Search results for: fuzzy integrated evaluation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9641

Search results for: fuzzy integrated evaluation

9131 Prediction of Compressive Strength in Geopolymer Composites by Adaptive Neuro Fuzzy Inference System

Authors: Mehrzad Mohabbi Yadollahi, Ramazan Demirboğa, Majid Atashafrazeh

Abstract:

Geopolymers are highly complex materials which involve many variables which makes modeling its properties very difficult. There is no systematic approach in mix design for Geopolymers. Since the amounts of silica modulus, Na2O content, w/b ratios and curing time have a great influence on the compressive strength an ANFIS (Adaptive neuro fuzzy inference system) method has been established for predicting compressive strength of ground pumice based Geopolymers and the possibilities of ANFIS for predicting the compressive strength has been studied. Consequently, ANFIS can be used for geopolymer compressive strength prediction with acceptable accuracy.

Keywords: geopolymer, ANFIS, compressive strength, mix design

Procedia PDF Downloads 847
9130 Study of Two MPPTs for Photovoltaic Systems Using Controllers Based in Fuzzy Logic and Sliding Mode

Authors: N. Ould cherchali, M. S. Boucherit, L. Barazane, A. Morsli

Abstract:

Photovoltaic power is widely used to supply isolated or unpopulated areas (lighting, pumping, etc.). Great advantage is that this source is inexhaustible, it offers great safety in use and it is clean. But the dynamic models used to describe a photovoltaic system are complicated and nonlinear and due to nonlinear I-V and P–V characteristics of photovoltaic generators, a maximum power point tracking technique (MPPT) is required to maximize the output power. In this paper, two online techniques of maximum power point tracking using robust controller for photovoltaic systems are proposed, the first technique use fuzzy logic controller (FLC) and the second use sliding mode controller (SMC) for photovoltaic systems. The two maximum power point tracking controllers receive the partial derivative of power as inputs, and the output is the duty cycle corresponding to maximum power. A Photovoltaic generator with Boost converter is developed using MATLAB/Simulink to verify the preferences of the proposed techniques. SMC technique provides a good tracking speed in fast changing irradiation and when the irradiation changes slowly or is constant the panel power of FLC technique presents a much smoother signal with less fluctuations.

Keywords: fuzzy logic controller, maximum power point, photovoltaic system, tracker, sliding mode controller

Procedia PDF Downloads 542
9129 Fuzzy Inference System for Determining Collision Risk of Ship in Madura Strait Using Automatic Identification System

Authors: Emmy Pratiwi, Ketut B. Artana, A. A. B. Dinariyana

Abstract:

Madura Strait is considered as one of the busiest shipping channels in Indonesia. High vessel traffic density in Madura Strait gives serious threat due to navigational safety in this area, i.e. ship collision. This study is necessary as an attempt to enhance the safety of marine traffic. Fuzzy inference system (FIS) is proposed to calculate risk collision of ships. Collision risk is evaluated based on ship domain, Distance to Closest Point of Approach (DCPA), and Time to Closest Point of Approach (TCPA). Data were collected by utilizing Automatic Identification System (AIS). This study considers several ships’ domain models to give the characteristic of marine traffic in the waterways. Each encounter in the ship domain is analyzed to obtain the level of collision risk. Risk level of ships, as the result in this study, can be used as guidance to avoid the accident, providing brief description about safety traffic in Madura Strait and improving the navigational safety in the area.

Keywords: automatic identification system, collision risk, DCPA, fuzzy inference system, TCPA

Procedia PDF Downloads 547
9128 A Framework for Early Differential Diagnosis of Tropical Confusable Diseases Using the Fuzzy Cognitive Map Engine

Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji

Abstract:

The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.

Keywords: medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis

Procedia PDF Downloads 315
9127 Design of Cloud Service Brokerage System Intermediating Integrated Services in Multiple Cloud Environment

Authors: Dongjae Kang, Sokho Son, Jinmee Kim

Abstract:

Cloud service brokering is a new service paradigm that provides interoperability and portability of application across multiple Cloud providers. In this paper, we designed cloud service brokerage system, any broker, supporting integrated service provisioning and SLA based service life cycle management. For the system design, we introduce the system concept and whole architecture, details of main components and use cases of primary operations in the system. These features ease the Cloud service provider and customer’s concern and support new Cloud service open market to increase cloud service profit and prompt Cloud service echo system in cloud computing related area.

Keywords: cloud service brokerage, multiple Clouds, Integrated service provisioning, SLA, network service

Procedia PDF Downloads 481
9126 Fuzzy Adaptive Control of an Intelligent Hybrid HPS (Pvwindbat), Grid Power System Applied to a Dwelling

Authors: A. Derrouazin, N. Mekkakia-M, R. Taleb, M. Helaimi, A. Benbouali

Abstract:

Nowadays the use of different sources of renewable energy for the production of electricity is the concern of everyone, as, even impersonal domestic use of the electricity in isolated sites or in town. As the conventional sources of energy are shrinking, a need has arisen to look for alternative sources of energy with more emphasis on its optimal use. This paper presents design of a sustainable Hybrid Power System (PV-Wind-Storage) assisted by grid as supplementary sources applied to case study residential house, to meet its entire energy demand. A Fuzzy control system model has been developed to optimize and control flow of power from these sources. This energy requirement is mainly fulfilled from PV and Wind energy stored in batteries module for critical load of a residential house and supplemented by grid for base and peak load. The system has been developed for maximum daily households load energy of 3kWh and can be scaled to any higher value as per requirement of individual /community house ranging from 3kWh/day to 10kWh/day, as per the requirement. The simulation work, using intelligent energy management, has resulted in an optimal yield leading to average reduction in cost of electricity by 50% per day.

Keywords: photovoltaic (PV), wind turbine, battery, microcontroller, fuzzy control (FC), Matlab

Procedia PDF Downloads 645
9125 Implementation of an Undergraduate Integrated Biology and Chemistry Course

Authors: Jayson G. Balansag

Abstract:

An integrated biology and chemistry (iBC) course for freshmen college students was developed in University of Delaware. This course will prepare students to (1) become interdisciplinary thinkers in the field of biology and (2) collaboratively work with others from multiple disciplines in the future. This paper documents and describes the implementation of the course. The information gathered from reading literature, classroom observations, and interviews were used to carry out the purpose of this paper. The major goal of the iBC course is to align the concepts between Biology and Chemistry, so that students can draw science concepts from both disciplines which they can apply in their interdisciplinary researches. This course is offered every fall and spring semesters of each school year. Students enrolled in Biology are also enrolled in Chemistry during the same semester. The iBC is composed of lectures, laboratories, studio sessions, and workshops and is taught by the faculty from the biology and chemistry departments. In addition, the preceptors, graduate teaching assistants, and studio fellows facilitate the laboratory and studio sessions. These roles are interdependent with each other. The iBC can be used as a model for higher education institutions who wish to implement an integrated biology course.

Keywords: integrated biology and chemistry, integration, interdisciplinary research, new biology, undergraduate science education

Procedia PDF Downloads 238
9124 Scour Depth Prediction around Bridge Piers Using Neuro-Fuzzy and Neural Network Approaches

Authors: H. Bonakdari, I. Ebtehaj

Abstract:

The prediction of scour depth around bridge piers is frequently considered in river engineering. One of the key aspects in efficient and optimum bridge structure design is considered to be scour depth estimation around bridge piers. In this study, scour depth around bridge piers is estimated using two methods, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). Therefore, the effective parameters in scour depth prediction are determined using the ANN and ANFIS methods via dimensional analysis, and subsequently, the parameters are predicted. In the current study, the methods’ performances are compared with the nonlinear regression (NLR) method. The results show that both methods presented in this study outperform existing methods. Moreover, using the ratio of pier length to flow depth, ratio of median diameter of particles to flow depth, ratio of pier width to flow depth, the Froude number and standard deviation of bed grain size parameters leads to optimal performance in scour depth estimation.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), bridge pier, scour depth, nonlinear regression (NLR)

Procedia PDF Downloads 215
9123 Development of a Value Evaluation Model of Highway Box-Girder Bridge

Authors: Hao Hsi Tseng

Abstract:

Taiwan’s infrastructure is gradually deteriorating, while resources for maintenance and replacement are increasingly limited, raising the urgent need for methods for maintaining existing infrastructure within constrained budgets. Infrastructure value evaluation is used to enhance the efficiency of infrastructure maintenance work, allowing administrators to quickly assess the maintenance needs and performance by observing variation in infrastructure value. This research establishes a value evaluation model for Taiwan’s highway box girder bridges. The operating mechanism and process of the model are illustrated in a practical case.

Keywords: box girder bridge, deterioration, infrastructure, maintenance, value evaluation

Procedia PDF Downloads 186
9122 An Economic Order Quantity Model for Deteriorating Items with Ramp Type Demand, Time Dependent Holding Cost and Price Discount Offered on Backorders

Authors: Arjun Paul, Adrijit Goswami

Abstract:

In our present work, an economic order quantity inventory model with shortages is developed where holding cost is expressed as linearly increasing function of time and demand rate is a ramp type function of time. The items considered in the model are deteriorating in nature so that a small fraction of the items is depleted with the passage of time. In order to consider a more realistic situation, the deterioration rate is assumed to follow a continuous uniform distribution with the parameters involved being triangular fuzzy numbers. The inventory manager offers his customer a discount in case he is willing to backorder his demand when there is a stock-out. The optimum ordering policy and the optimum discount offered for each backorder are determined by minimizing the total cost in a replenishment interval. For better illustration of our proposed model in both the crisp and fuzzy sense and for providing richer insights, a numerical example is cited to exemplify the policy and to analyze the sensitivity of the model parameters.

Keywords: fuzzy deterioration rate, price discount on backorder, ramp type demand, shortage, time varying holding cost

Procedia PDF Downloads 192
9121 A Tool for Facilitating an Institutional Risk Profile Definition

Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

Abstract:

This paper presents an approach for the easy creation of an institutional risk profile for endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support risk factors set up with just the most important values that are important for a particular organisation. Subsequently, the risk profile employs fuzzy models and associated configurations for the file format metadata aggregator to support digital preservation experts with a semi-automatic estimation of endangerment level for file formats. Our goal is to make use of a domain expert knowledge base aggregated from a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation and analysis of risk factors for a requried dimension. The proposed methods improve the visibility of risk factor information and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and automatically aggregated file format metadata from linked open data sources. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: digital information management, file format, endangerment analysis, fuzzy models

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9120 MASCOT: Design and Development of an Interactive Self-Evaluation Tool for Students’ Thinking Complexity

Authors: Xin Gao, Jun Wu

Abstract:

'In Dialogue with Humanity’ and ‘In Dialogue with Nature’ are two compulsory General Education Foundation (GEF) courses for all undergraduates at the Chinese University of Hong Kong (CUHK). These courses aim to enrich students’ intellectual pursuits and enhance their thinking capabilities through classic readings. To better understand and evaluate students’ thinking habits and abilities, GEF introduced Narrative Qualitative Analysis (NQA) in 2014 and has continued the study since then. Through the NQA study, a two-way evaluation scheme has been developed, including both student self-evaluation and teacher evaluation. This study will first introduce the theoretical background and research framework of the NQA study and then focus on student self-evaluation. An interactive online application, MASCOT, has been developed to facilitate students’ self-evaluation of their own thinking complexity. In this presentation, the design and development of MASCOT will be explained, and the main results will be reported when applying it in classroom teaching. An obvious discrepancy has been observed between students’ self-evaluations and teachers’ evaluations.

Keywords: narrative qualitative analysis, thinking complexity, student self-evaluation, interactive online application

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9119 Analysis of Two Methods to Estimation Stochastic Demand in the Vehicle Routing Problem

Authors: Fatemeh Torfi

Abstract:

Estimation of stochastic demand in physical distribution in general and efficient transport routs management in particular is emerging as a crucial factor in urban planning domain. It is particularly important in some municipalities such as Tehran where a sound demand management calls for a realistic analysis of the routing system. The methodology involved critically investigating a fuzzy least-squares linear regression approach (FLLRs) to estimate the stochastic demands in the vehicle routing problem (VRP) bearing in mind the customer's preferences order. A FLLR method is proposed in solving the VRP with stochastic demands. Approximate-distance fuzzy least-squares (ADFL) estimator ADFL estimator is applied to original data taken from a case study. The SSR values of the ADFL estimator and real demand are obtained and then compared to SSR values of the nominal demand and real demand. Empirical results showed that the proposed methods can be viable in solving problems under circumstances of having vague and imprecise performance ratings. The results further proved that application of the ADFL was realistic and efficient estimator to face the stochastic demand challenges in vehicle routing system management and solve relevant problems.

Keywords: fuzzy least-squares, stochastic, location, routing problems

Procedia PDF Downloads 431
9118 Bridge Members Segmentation Algorithm of Terrestrial Laser Scanner Point Clouds Using Fuzzy Clustering Method

Authors: Donghwan Lee, Gichun Cha, Jooyoung Park, Junkyeong Kim, Seunghee Park

Abstract:

3D shape models of the existing structure are required for many purposes such as safety and operation management. The traditional 3D modeling methods are based on manual or semi-automatic reconstruction from close-range images. It occasions great expense and time consuming. The Terrestrial Laser Scanner (TLS) is a common survey technique to measure quickly and accurately a 3D shape model. This TLS is used to a construction site and cultural heritage management. However there are many limits to process a TLS point cloud, because the raw point cloud is massive volume data. So the capability of carrying out useful analyses is also limited with unstructured 3-D point. Thus, segmentation becomes an essential step whenever grouping of points with common attributes is required. In this paper, members segmentation algorithm was presented to separate a raw point cloud which includes only 3D coordinates. This paper presents a clustering approach based on a fuzzy method for this objective. The Fuzzy C-Means (FCM) is reviewed and used in combination with a similarity-driven cluster merging method. It is applied to the point cloud acquired with Lecia Scan Station C10/C5 at the test bed. The test-bed was a bridge which connects between 1st and 2nd engineering building in Sungkyunkwan University in Korea. It is about 32m long and 2m wide. This bridge was used as pedestrian between two buildings. The 3D point cloud of the test-bed was constructed by a measurement of the TLS. This data was divided by segmentation algorithm for each member. Experimental analyses of the results from the proposed unsupervised segmentation process are shown to be promising. It can be processed to manage configuration each member, because of the segmentation process of point cloud.

Keywords: fuzzy c-means (FCM), point cloud, segmentation, terrestrial laser scanner (TLS)

Procedia PDF Downloads 228
9117 Opportunity Integrated Assessment Facilitating Critical Thinking and Science Process Skills Measurement on Acid Base Matter

Authors: Anggi Ristiyana Puspita Sari, Suyanta

Abstract:

To recognize the importance of the development of critical thinking and science process skills, the instrument should give attention to the characteristics of chemistry. Therefore, constructing an accurate instrument for measuring those skills is important. However, the integrated instrument assessment is limited in number. The purpose of this study is to validate an integrated assessment instrument for measuring students’ critical thinking and science process skills on acid base matter. The development model of the test instrument adapted McIntire model. The sample consisted of 392 second grade high school students in the academic year of 2015/2016 in Yogyakarta. Exploratory factor analysis (EFA) was conducted to explore construct validity, whereas content validity was substantiated by Aiken’s formula. The result shows that the KMO test is 0.714 which indicates sufficient items for each factor and the Bartlett test is significant (a significance value of less than 0.05). Furthermore, content validity coefficient which is based on 8 expert judgments is obtained at 0.85. The findings support the integrated assessment instrument to measure critical thinking and science process skills on acid base matter.

Keywords: acid base matter, critical thinking skills, integrated assessment instrument, science process skills, validity

Procedia PDF Downloads 318
9116 Rule-Based Mamdani Type Fuzzy Modeling of Performances of Anode Side of Proton Exchange Membrane Fuel Cell Spin-Coated with Yttria-Stabilized Zirconia

Authors: Sadık Ata, Kevser Dincer

Abstract:

In this study, performance of proton exchange membrane (PEM) fuel cell was experimentally investigated and modelled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modelling technique. Coating on the anode side of the PEM fuel cell was accomplished with the spin method by using Yttria-stabilized zirconia (YSZ). Input parameters voltage density (V/cm2), and current density (A/cm2), temperature (°C), time (s); output parameter power density (W/cm2) were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), Positive Medium (L6), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between experimental data and RBMTF is done by using statistical methods like absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF can be successfully used for the analysis of performance of PEM fuel cell.

Keywords: proton exchange membrane (PEM), fuel cell, rule-based Mamdani-type fuzzy (RMBTF) modeling, yttria-stabilized zirconia (YSZ)

Procedia PDF Downloads 359
9115 Feminist Evaluation: The Case of Mahatma Gandhi National Rural Employment Guarantee Act

Authors: Salam Abukhadrah

Abstract:

This research advocates for the use of feminist evaluation (FE) as a tool of great potential in policy and program assessment in relation to women’s empowerment. This research explores the journey of women’s place into the evaluation and international development. Moreover, this research presents a case example of the use of FE on the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), in Ganaparthi village in rural India, in Andhra Pradesh state (AP). This evaluation is formed on the basis of women’s empowerment framework that seeks to examine empowerment as a process and an end in itself rather than as just simplified quantifiable outcomes. This framework is used to conduct in-depth semi-structured interviews that are later cross-validated by a focus group discussion. In addition, this evaluation draws on secondary data from the MGNREGA website and on extracted data from the National Family Health Survey of AP.

Keywords: feminist evaluation, MGNREGA, women’s empowerment, case example, India

Procedia PDF Downloads 140
9114 The Intention to Use Telecare in People of Fall Experience: Application of Fuzzy Neural Network

Authors: Jui-Chen Huang, Shou-Hsiung Cheng

Abstract:

This study examined their willingness to use telecare for people who have had experience falling in the last three months in Taiwan. This study adopted convenience sampling and a structural questionnaire to collect data. It was based on the definition and the constructs related to the Health Belief Model (HBM). HBM is comprised of seven constructs: perceived benefits (PBs), perceived disease threat (PDT), perceived barriers of taking action (PBTA), external cues to action (ECUE), internal cues to action (ICUE), attitude toward using (ATT), and behavioral intention to use (BI). This study adopted Fuzzy Neural Network (FNN) to put forward an effective method. It shows the dependence of ATT on PB, PDT, PBTA, ECUE, and ICUE. The training and testing data RMSE (root mean square error) are 0.028 and 0.166 in the FNN, respectively. The training and testing data RMSE are 0.828 and 0.578 in the regression model, respectively. On the other hand, as to the dependence of ATT on BI, as presented in the FNN, the training and testing data RMSE are 0.050 and 0.109, respectively. The training and testing data RMSE are 0.529 and 0.571 in the regression model, respectively. The results show that the FNN method is better than the regression analysis. It is an effective and viable good way.

Keywords: fall, fuzzy neural network, health belief model, telecare, willingness

Procedia PDF Downloads 194
9113 Improved Particle Swarm Optimization with Cellular Automata and Fuzzy Cellular Automata

Authors: Ramin Javadzadeh

Abstract:

The particle swarm optimization are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Particle swarm optimization is introduced for the first time to overcome its problems. The fuzzy cellular automata is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the Particle swarm optimization algorithms.

Keywords: cellular automata, cellular learning automata, local search, optimization, particle swarm optimization

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9112 An Implementation of Fuzzy Logic Technique for Prediction of the Power Transformer Faults

Authors: Omar M. Elmabrouk., Roaa Y. Taha., Najat M. Ebrahim, Sabbreen A. Mohammed

Abstract:

Power transformers are the most crucial part of power electrical system, distribution and transmission grid. This part is maintained using predictive or condition-based maintenance approach. The diagnosis of power transformer condition is performed based on Dissolved Gas Analysis (DGA). There are five main methods utilized for analyzing these gases. These methods are International Electrotechnical Commission (IEC) gas ratio, Key Gas, Roger gas ratio, Doernenburg, and Duval Triangle. Moreover, due to the importance of the transformers, there is a need for an accurate technique to diagnose and hence predict the transformer condition. The main objective of this technique is to avoid the transformer faults and hence to maintain the power electrical system, distribution and transmission grid. In this paper, the DGA was utilized based on the data collected from the transformer records available in the General Electricity Company of Libya (GECOL) which is located in Benghazi-Libya. The Fuzzy Logic (FL) technique was implemented as a diagnostic approach based on IEC gas ratio method. The FL technique gave better results and approved to be used as an accurate prediction technique for power transformer faults. Also, this technique is approved to be a quite interesting for the readers and the concern researchers in the area of FL mathematics and power transformer.

Keywords: dissolved gas-in-oil analysis, fuzzy logic, power transformer, prediction

Procedia PDF Downloads 139
9111 Tree-Based Inference for Regionalization: A Comparative Study of Global Topological Perturbation Methods

Authors: Orhun Aydin, Mark V. Janikas, Rodrigo Alves, Renato Assuncao

Abstract:

In this paper, a tree-based perturbation methodology for regionalization inference is presented. Regionalization is a constrained optimization problem that aims to create groups with similar attributes while satisfying spatial contiguity constraints. Similar to any constrained optimization problem, the spatial constraint may hinder convergence to some global minima, resulting in spatially contiguous members of a group with dissimilar attributes. This paper presents a general methodology for rigorously perturbing spatial constraints through the use of random spanning trees. The general framework presented can be used to quantify the effect of the spatial constraints in the overall regionalization result. We compare several types of stochastic spanning trees used in inference problems such as fuzzy regionalization and determining the number of regions. Performance of stochastic spanning trees is juxtaposed against the traditional permutation-based hypothesis testing frequently used in spatial statistics. Inference results for fuzzy regionalization and determining the number of regions is presented on the Local Area Personal Incomes for Texas Counties provided by the Bureau of Economic Analysis.

Keywords: regionalization, constrained clustering, probabilistic inference, fuzzy clustering

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9110 Risk Assessment of Natural Gas Pipelines in Coal Mined Gobs Based on Bow-Tie Model and Cloud Inference

Authors: Xiaobin Liang, Wei Liang, Laibin Zhang, Xiaoyan Guo

Abstract:

Pipelines pass through coal mined gobs inevitably in the mining area, the stability of which has great influence on the safety of pipelines. After extensive literature study and field research, it was found that there are a few risk assessment methods for coal mined gob pipelines, and there is a lack of data on the gob sites. Therefore, the fuzzy comprehensive evaluation method is widely used based on expert opinions. However, the subjective opinions or lack of experience of individual experts may lead to inaccurate evaluation results. Hence the accuracy of the results needs to be further improved. This paper presents a comprehensive approach to achieve this purpose by combining bow-tie model and cloud inference. The specific evaluation process is as follows: First, a bow-tie model composed of a fault tree and an event tree is established to graphically illustrate the probability and consequence indicators of pipeline failure. Second, the interval estimation method can be scored in the form of intervals to improve the accuracy of the results, and the censored mean algorithm is used to remove the maximum and minimum values of the score to improve the stability of the results. The golden section method is used to determine the weight of the indicators and reduce the subjectivity of index weights. Third, the failure probability and failure consequence scores of the pipeline are converted into three numerical features by using cloud inference. The cloud inference can better describe the ambiguity and volatility of the results which can better describe the volatility of the risk level. Finally, the cloud drop graphs of failure probability and failure consequences can be expressed, which intuitively and accurately illustrate the ambiguity and randomness of the results. A case study of a coal mine gob pipeline carrying natural gas has been investigated to validate the utility of the proposed method. The evaluation results of this case show that the probability of failure of the pipeline is very low, the consequences of failure are more serious, which is consistent with the reality.

Keywords: bow-tie model, natural gas pipeline, coal mine gob, cloud inference

Procedia PDF Downloads 248
9109 Control Strategy for Two-Mode Hybrid Electric Vehicle by Using Fuzzy Controller

Authors: Jia-Shiun Chen, Hsiu-Ying Hwang

Abstract:

Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.

Keywords: hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control

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9108 Rational Allocation of Resources in Water Infrastructure Development Projects

Authors: M. Macchiaroli, V. Pellecchia, L. Dolores

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Within any European and world model of management of the integrated water service (in Italy only since 2012 is regulated by a national Authority, that is ARERA), a significant part is covered by the development of assets in terms of hydraulic networks and wastewater collection networks, including all their relative building works. The process of selecting the investments to be made starts from the preventive analysis of critical issues (water losses, unserved areas, low service standards, etc.) who occur in the managed territory of the Operator. Through the Program of Interventions (Provision by ARERA n. 580/2019/R/idr), the Operator provides to program the projects that can meet the emerged needs to determine the improvement of the water service levels. This phase (analyzed and solved by the author with a work published in 2019) involves the use of evaluation techniques (cost-benefit analysis, multi-criteria, and multi-objective techniques, neural networks, etc.) useful in selecting the most appropriate design answers to the different criticalities. However, at this point, the problem of establishing the time priorities between the various works deemed necessary remains open. That is, it is necessary to hierarchize the investments. In this decision-making moment, the interests of the private Operator are often opposed, which favors investments capable of generating high profitability, compared to those of the public controller (ARERA), which favors investments in greater social impact. In support of the concertation between these two actors, the protocol set out in the research has been developed, based on the AHP and capable of borrowing from the programmatic documents an orientation path for the settlement of the conflict. The protocol is applied to a case study of the Campania Region in Italy and has been professionally applied in the shared decision process between the manager and the local Authority.

Keywords: analytic hierarchy process, decision making, economic evaluation of projects, integrated water service

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9107 E-Hailing Taxi Industry Management Mode Innovation Based on the Credit Evaluation

Authors: Yuan-lin Liu, Ye Li, Tian Xia

Abstract:

There are some shortcomings in Chinese existing taxi management modes. This paper suggests to establish the third-party comprehensive information management platform and put forward an evaluation model based on credit. Four indicators are used to evaluate the drivers’ credit, they are passengers’ evaluation score, driving behavior evaluation, drivers’ average bad record number, and personal credit score. A weighted clustering method is used to achieve credit level evaluation for taxi drivers. The management of taxi industry is based on the credit level, while the grade of the drivers is accorded to their credit rating. Credit rating determines the cost, income levels, the market access, useful period of license and the level of wage and bonus, as well as violation fine. These methods can make the credit evaluation effective. In conclusion, more credit data will help to set up a more accurate and detailed classification standard library.

Keywords: credit, mobile internet, e-hailing taxi, management mode, weighted cluster

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9106 Utilization of Multi-Criteria Evaluation in Forensic Engineering and the Expertise outside Wall Subsystem

Authors: Tomas Barnak, Libor Matejka

Abstract:

The aim of this study is to create a standard application using multi-criteria evaluation in the field of forensic engineering. This situation can occur in the professional assessment in several cases such as when it is necessary to consider more criteria variant of the structural subsystems, more variants according to several criteria based on a court claim, which requires expert advice. A problematic situation arises when it is necessary to clearly determine the ranking of the options according to established criteria, and reduce subjective evaluation. For the procurement in the field of construction which is based on the prepared text of the law not only economic criteria but also technical, technological and environmental criteria will be determined. This fact substantially changes the style of evaluation of individual bids. For the above-mentioned needs of procurement, the unification of expert’s decisions and the use of multi-criteria assessment seem to be a reasonable option. In the case of experimental verification when using multi-criteria evaluation of alternatives construction subsystem the economic, technical, technological and environmental criteria will be compared. The core of the solution is to compare a selected number of set criteria, application methods and evaluation weighting based on the weighted values assigned to each of the criteria to use multi-criteria evaluation methods. The sequence of individual variations is determined by the evaluation of the importance of the values of corresponding criteria concerning expertise in the problematic of outside wall constructional subsystems.

Keywords: criteria, expertise, multi-criteria evaluation, outside wall subsystems

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9105 Knowledge-Driven Decision Support System Based on Knowledge Warehouse and Data Mining by Improving Apriori Algorithm with Fuzzy Logic

Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

Abstract:

In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

Procedia PDF Downloads 328
9104 Multi-Criteria Evaluation of IDS Architectures in Cloud Computing

Authors: Elmahdi Khalil, Saad Enniari, Mostapha Zbakh

Abstract:

Cloud computing promises to increase innovation and the velocity with witch applications are deployed, all while helping any enterprise meet most IT service needs at a lower total cost of ownership and higher return investment. As the march of cloud continues, it brings both new opportunities and new security challenges. To take advantages of those opportunities while minimizing risks, we think that Intrusion Detection Systems (IDS) integrated in the cloud is one of the best existing solutions nowadays in the field. The concept of intrusion detection was known since past and was first proposed by a well-known researcher named Anderson in 1980's. Since that time IDS's are evolving. Although, several efforts has been made in the area of Intrusion Detection systems for cloud computing environment, many attacks still prevail. Therefore, the work presented in this paper proposes a multi criteria analysis and a comparative study between several IDS architectures designated to work in a cloud computing environments. To achieve this objective, in the first place we will search in the state of the art of several consistent IDS architectures designed to work in a cloud environment. Whereas, in a second step we will establish the criteria that will be useful for the evaluation of architectures. Later, using the approach of multi criteria decision analysis Mac Beth (Measuring Attractiveness by a Categorical Based Evaluation Technique we will evaluate the criteria and assign to each one the appropriate weight according to their importance in the field of IDS architectures in cloud computing. The last step is to evaluate architectures against the criteria and collecting results of the model constructed in the previous steps.

Keywords: cloud computing, cloud security, intrusion detection/prevention system, multi-criteria decision analysis

Procedia PDF Downloads 467
9103 Stabilization Control of the Nonlinear AIDS Model Based on the Theory of Polynomial Fuzzy Control Systems

Authors: Shahrokh Barati

Abstract:

In this paper, we introduced AIDS disease at first, then proposed dynamic model illustrate its progress, after expression of a short history of nonlinear modeling by polynomial phasing systems, we considered the stability conditions of the systems, which contained a huge amount of researches in order to modeling and control of AIDS in dynamic nonlinear form, in this approach using a frame work of control any polynomial phasing modeling system which have been generalized by part of phasing model of T-S, in order to control the system in better way, the stability conditions were achieved based on polynomial functions, then we focused to design the appropriate controller, firstly we considered the equilibrium points of system and their conditions and in order to examine changes in the parameters, we presented polynomial phase model that was the generalized approach rather than previous Takagi Sugeno models, then with using case we evaluated the equations in both open loop and close loop and with helping the controlling feedback, the close loop equations of system were calculated, to simulate nonlinear model of AIDS disease, we used polynomial phasing controller output that was capable to make the parameters of a nonlinear system to follow a sustainable reference model properly.

Keywords: polynomial fuzzy, AIDS, nonlinear AIDS model, fuzzy control systems

Procedia PDF Downloads 465
9102 Integrated Water Resources Management to Ensure Water Security of Arial Khan River Catchment

Authors: Abul Kalam Azad

Abstract:

Water security has become an increasingly important issue both at the national and international levels. Bangladesh having an abundance of water during monsoon while the shortage of water during the dry season is far from being water secured. Though water security has been discussed discretely at a different level but a holistic effort to ensure water security is yet to be made. The elements of water security such as sectoral demands of water, conflicting requirements amongst the sectors, balancing between demand and supply including the quality of water can best be understood and managed in a catchment as it is the standard functioning unit. The Arial Khan River catchment consists of parts of Faridpur, Madaripur, Shariatpur and Barishal districts have all the components of water demands such as agriculture, domestic, commercial, industrial, forestry, fisheries, navigation or recreation and e-flow requirements. Based on secondary and primary data, water demands of various sectors have been determined. CROPWAT 8.0 has been used to determine the Agricultural Water Demand. Mean Annual Flow (MAF) and Flow Duration Curve (FDC) have been used to determine the e-flow requirements. Water Evaluation and Planning System (WEAP) based decision support tool as part of Integrated Water Resources Management (IWRM) has been utilized for ensuring the water security of the Arial Khan River catchment. Studies and practice around the globe connected with water security were consulted to mitigate the pressure on demand and supply including the options available to ensure the water security. Combining all the information, a framework for ensuring water security has been suggested for Arial Khan River catchment which can further be projected to river basin as well as for the country. This will assist planners and researchers to introduce the model for integrated water resources management of any catchment/river basins.

Keywords: water security, water demand, water supply, WEAP, CROPWAT

Procedia PDF Downloads 12