Search results for: Fuzzy cost.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2969

Search results for: Fuzzy cost.

2309 Automatic Detection of Proliferative Cells in Immunohistochemically Images of Meningioma Using Fuzzy C-Means Clustering and HSV Color Space

Authors: Vahid Anari, Mina Bakhshi

Abstract:

Visual search and identification of immunohistochemically stained tissue of meningioma was performed manually in pathologic laboratories to detect and diagnose the cancers type of meningioma. This task is very tedious and time-consuming. Moreover, because of cell's complex nature, it still remains a challenging task to segment cells from its background and analyze them automatically. In this paper, we develop and test a computerized scheme that can automatically identify cells in microscopic images of meningioma and classify them into positive (proliferative) and negative (normal) cells. Dataset including 150 images are used to test the scheme. The scheme uses Fuzzy C-means algorithm as a color clustering method based on perceptually uniform hue, saturation, value (HSV) color space. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: Positive cell, color segmentation, HSV color space, immunohistochemistry, meningioma, thresholding, fuzzy c-means.

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2308 A New Framework for Evaluation and Prioritization of Suppliers using a Hierarchical Fuzzy TOPSIS

Authors: Mohammad Taghi Taghavifard, Danial Mirheydari

Abstract:

This paper suggests an algorithm for the evaluation and selection of suppliers. At the beginning, all the needed materials and services used by the organization were identified and categorized with regard to their nature by ABC method. Afterwards, in order to reduce risk factors and maximize the organization's profit, purchase strategies were determined. Then, appropriate criteria were identified for primary evaluation of suppliers applying to the organization. The output of this stage was a list of suppliers qualified by the organization to participate in its tenders. Subsequently, considering a material in particular, appropriate criteria on the ordering of the mentioned material were determined, taking into account the particular materials' specifications as well as the organization's needs. Finally, for the purpose of validation and verification of the proposed model, it was applied to Mobarakeh Steel Company (MSC), the qualified suppliers of this Company are ranked by the means of a Hierarchical Fuzzy TOPSIS method. The obtained results show that the proposed algorithm is quite effective, efficient and easy to apply.

Keywords: ABC analysis, Hierarchical Fuzzy TOPSIS, Primary supplier evaluation, Purchasing strategy, supplier selection

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2307 Factors Contributing to Building Construction Project’s Cost Overrun in Jordan

Authors: Ghaleb Y. Abbasi, Sufyan Al-Mrayat

Abstract:

This study examined the contribution of 36 factors to building construction project’s cost overrun in Jordan. A questionnaire was distributed to a random sample of 350 stakeholders comprised of owners, consultants, and contractors, of which 285 responded. SPSS analysis was conducted to identify the top five causes of cost overrun, which were a large number of variation orders, inadequate quantities provided in the contract, misunderstanding of the project plan, incomplete bid documents, and choosing the lowest price in the contract bidding. There was an agreement among the study participants in ranking the factors contributing to cost overrun, which indicated that these factors were very commonly encountered in most construction projects in Jordan. Thus, it is crucial to enhance the collaboration among the different project stakeholders to understand the project’s objectives and set a realistic plan that takes into consideration all the factors that might influence the project cost, which might eventually prevent cost overrun.

Keywords: Cost, overrun, building construction projects, Jordan.

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2306 Transmission Expansion Planning Considering Network Adequacy and Investment Cost Limitation using Genetic Algorithm

Authors: M. Mahdavi, E. Mahdavi

Abstract:

In this research, STNEP is being studied considering network adequacy and limitation of investment cost by decimal codification genetic algorithm (DCGA). The goal is obtaining the maximum of network adequacy with lowest expansion cost for a specific investment. Finally, the proposed idea is applied to the Garvers 6-bus network. The results show that considering the network adequacy for solution of STNEP problem is caused that among of expansion plans for a determined investment, configuration which has relatively lower expansion cost and higher adequacy is proposed by GA based method. Finally, with respect to the curve of adequacy versus expansion cost it can be said that more optimal configurations for expansion of network are obtained with lower investment costs.

Keywords: TNEP, Network Adequacy, Investment Cost, GA

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2305 Monte Carlo Analysis and Fuzzy Sets for Uncertainty Propagation in SIS Performance Assessment

Authors: Fares Innal, Yves Dutuit, Mourad Chebila

Abstract:

The object of this work is the probabilistic performance evaluation of safety instrumented systems (SIS), i.e. the average probability of dangerous failure on demand (PFDavg) and the average frequency of failure (PFH), taking into account the uncertainties related to the different parameters that come into play: failure rate (λ), common cause failure proportion (β), diagnostic coverage (DC)... This leads to an accurate and safe assessment of the safety integrity level (SIL) inherent to the safety function performed by such systems. This aim is in keeping with the requirement of the IEC 61508 standard with respect to handling uncertainty. To do this, we propose an approach that combines (1) Monte Carlo simulation and (2) fuzzy sets. Indeed, the first method is appropriate where representative statistical data are available (using pdf of the relating parameters), while the latter applies in the case characterized by vague and subjective information (using membership function). The proposed approach is fully supported with a suitable computer code.

Keywords: Fuzzy sets, Monte Carlo simulation, Safety instrumented system, Safety integrity level.

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2304 Vibration Control of a Cantilever Beam Using a Tunable Vibration Absorber Embedded with ER Fluids

Authors: Chih-Jer Lin, Chun-Ying Lee, Chiang-Ho Cheng, Geng-Fung Chen

Abstract:

This paper investigates experimental studies on vibration suppression for a cantilever beam using an Electro-Rheological (ER) sandwich shock absorber. ER fluid (ERF) is a class of smart materials that can undergo significant reversible changes immediately in its rheological and mechanical properties under the influence of an applied electric field. Firstly, an ER sandwich beam is fabricated by inserting a starch-based ERF into a hollow composite beam. At the same time, experimental investigations are focused on the frequency response of the ERF sandwich beam. Second, the ERF sandwich beam is attached to a cantilever beam to become as a shock absorber. Finally, a fuzzy semi-active vibration control is designed to suppress the vibration of the cantilever beam via the ERF sandwich shock absorber. To check the consistency of the proposed fuzzy controller, the real-time implementation validated the performance of the controller.

Keywords: Electro-Rheological Fluid, Semi-active vibration control, shock absorber, fuzzy control, Real-time control.

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2303 Preliminary Views on the Determinants of the Cost of Capital for the Emergent Market of Romania

Authors: I. Ionascu, M. Ionascu, D.-A. Calu, L. Olimid

Abstract:

This paper investigates several factors affecting the cost of capital for listed Romanian companies. Although there is a large amount of literature investigating the drivers of the cost of capital internationally, there is currently little evidence from emergent markets. Based on a sample of 19 Romanian listed companies followed by financial analysts for the years 2008-2010, according to Thomson Reuters- I/B/E/S data base, the paper confirms the international trends, showing that size, corporate governance policies, and growth are negatively correlated with the cost of capital.

Keywords: Corporate governance, determinants of the cost of capital, emergent markets.

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2302 Combining Fuzzy Logic and Data Miningto Predict the Result of an EIA Review

Authors: Kevin Fong-Rey Liu, Jia-Shen Chen, Han-Hsi Liang, Cheng-Wu Chen, Yung-Shuen Shen

Abstract:

The purpose of determining impact significance is to place value on impacts. Environmental impact assessment review is a process that judges whether impact significance is acceptable or not in accordance with the scientific facts regarding environmental, ecological and socio-economical impacts described in environmental impact statements (EIS) or environmental impact assessment reports (EIAR). The first aim of this paper is to summarize the criteria of significance evaluation from the past review results and accordingly utilize fuzzy logic to incorporate these criteria into scientific facts. The second aim is to employ data mining technique to construct an EIS or EIAR prediction model for reviewing results which can assist developers to prepare and revise better environmental management plans in advance. The validity of the previous prediction model proposed by authors in 2009 is 92.7%. The enhanced validity in this study can attain 100.0%.

Keywords: Environmental impact assessment review, impactsignificance, fuzzy logic, data mining, classification tree.

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2301 Using Data Mining for Learning and Clustering FCM

Authors: Somayeh Alizadeh, Mehdi Ghazanfari, Mohammad Fathian

Abstract:

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show relations between essential components. In some FCM, there are more nodes, which related to each other and more nodes means more complex in system behaviors and analysis. In this paper, a novel learning method used to construct FCMs based on historical data and by using data mining and DEMATEL method, a new method defined to reduce nodes number. This method cluster nodes in FCM based on their cause and effect behaviors.

Keywords: Clustering, Data Mining, Fuzzy Cognitive Map(FCM), Learning.

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2300 Fuzzy Group Decision Making for the Assessment of Health-Care Waste Disposal Alternatives in Istanbul

Authors: Mehtap Dursun, E. Ertugrul Karsak, Melis Almula Karadayi

Abstract:

Disposal of health-care waste (HCW) is considered as an important environmental problem especially in large cities. Multiple criteria decision making (MCDM) techniques are apt to deal with quantitative and qualitative considerations of the health-care waste management (HCWM) problems. This research proposes a fuzzy multi-criteria group decision making approach with a multilevel hierarchical structure including qualitative as well as quantitative performance attributes for evaluating HCW disposal alternatives for Istanbul. Using the entropy weighting method, objective weights as well as subjective weights are taken into account to determine the importance weighting of quantitative performance attributes. The results obtained using the proposed methodology are thoroughly analyzed.

Keywords: Entropy weighting method, group decision making, health-care waste management, hierarchical fuzzy multi-criteriadecision making

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2299 A Cascaded Fuzzy Inference System for Dynamic Online Portals Customization

Authors: Erika Martinez Ramirez, Rene V. Mayorga

Abstract:

In our modern world, more physical transactions are being substituted by electronic transactions (i.e. banking, shopping, and payments), many businesses and companies are performing most of their operations through the internet. Instead of having a physical commerce, internet visitors are now adapting to electronic commerce (e-Commerce). The ability of web users to reach products worldwide can be greatly benefited by creating friendly and personalized online business portals. Internet visitors will return to a particular website when they can find the information they need or want easily. Dealing with this human conceptualization brings the incorporation of Artificial/Computational Intelligence techniques in the creation of customized portals. From these techniques, Fuzzy-Set technologies can make many useful contributions to the development of such a human-centered endeavor as e-Commerce. The main objective of this paper is the implementation of a Paradigm for the Intelligent Design and Operation of Human-Computer interfaces. In particular, the paradigm is quite appropriate for the intelligent design and operation of software modules that display information (such Web Pages, graphic user interfaces GUIs, Multimedia modules) on a computer screen. The human conceptualization of the user personal information is analyzed throughout a Cascaded Fuzzy Inference (decision-making) System to generate the User Ascribe Qualities, which identify the user and that can be used to customize portals with proper Web links.

Keywords: Fuzzy Logic, Internet, Electronic Commerce, Intelligent Portals, Electronic Shopping.

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2298 Integrating Life Cycle Uncertainties for Evaluating a Building Overall Cost

Authors: M. Arja, G. Sauce, B. Souyri

Abstract:

Overall cost is a significant consideration in any decision-making process. Although many studies were carried out on overall cost in construction, little has treated the uncertainties of real life cycle development. On the basis of several case studies, a feedback process was performed on the historical data of studied buildings. This process enabled to identify some factors causing uncertainty during the operational period. As a result, the research proposes a new method for assessing the overall cost during a part of the building-s life cycle taking account of the building actual value, its end-of-life value and the influence of the identified life cycle uncertainty factors. The findings are a step towards a higher level of reliability in overall cost evaluation taking account of some usually unexpected uncertainty factors.

Keywords: Asset management, building life cycle uncertainty, building value, overall cost.

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2297 Type–2 Fuzzy Programming for Optimizing the Heat Rate of an Industrial Gas Turbine via Absorption Chiller Technology

Authors: T. Ganesan, M. S. Aris, I. Elamvazuthi, Momen Kamal Tageldeen

Abstract:

Terms set in power purchase agreements (PPA) challenge power utility companies in balancing between the returns (from maximizing power production) and securing long term supply contracts at capped production. The production limitation set in the PPA has driven efforts to maximize profits through efficient and economic power production. In this paper, a combined industrial-scale gas turbine (GT) - absorption chiller (AC) system is considered to cool the GT air intake for reducing the plant’s heat rate (HR). This GT-AC system is optimized while considering power output limitations imposed by the PPA. In addition, the proposed formulation accounts for uncertainties in the ambient temperature using Type-2 fuzzy programming. Using the enhanced chaotic differential evolution (CEDE), the Pareto frontier was constructed and the optimization results are analyzed in detail.

Keywords: Absorption chillers, turbine inlet air cooling, power purchase agreement, multiobjective optimization, type-2 fuzzy programming, chaotic differential evolution.

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2296 A New Criterion Pose and Shape of Objects for Collision Risk Estimation

Authors: Do Hyeung Kim, Dae Hee Seo, Byung Doo Kim, Byung Gil Lee

Abstract:

As many recent researches being implemented in aviation and maritime aspects, strong doubts have been raised concerning the reliability of the estimation of collision risk. It is shown that using position and velocity of objects can lead to imprecise results. In this paper, therefore, a new approach to the estimation of collision risks using pose and shape of objects is proposed. Simulation results are presented validating the accuracy of the new criterion to adapt to collision risk algorithm based on fuzzy logic.

Keywords: Collision risk, Pose and shape, Fuzzy logic.

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2295 An Analysis of Activity-Based Costing in a Manufacturing System

Authors: Derya Eren Akyol, Gonca Tuncel, G. Mirac Bayhan

Abstract:

Activity-Based Costing (ABC) represents an alternative paradigm to traditional cost accounting system and it often provides more accurate cost information for decision making such as product pricing, product mix, and make-orbuy decisions. ABC models the causal relationships between products and the resources used in their production and traces the cost of products according to the activities through the use of appropriate cost drivers. In this paper, the implementation of the ABC in a manufacturing system is analyzed and a comparison with the traditional cost based system in terms of the effects on the product costs are carried out to highlight the difference between two costing methodologies. By using this methodology, a valuable insight into the factors that cause the cost is provided, helping to better manage the activities of the company.

Keywords: Activity-based costing, manufacturing systems, product costs, traditional costing.

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2294 Project Selection Using Fuzzy Group Analytic Network Process

Authors: Hamed Rafiei, Masoud Rabbani

Abstract:

This paper deals with the project selection problem. Project selection problem is one of the problems arose firstly in the field of operations research following some production concepts from primary product mix problem. Afterward, introduction of managerial considerations into the project selection problem have emerged qualitative factors and criteria to be regarded as well as quantitative ones. To overcome both kinds of criteria, an analytic network process is developed in this paper enhanced with fuzzy sets theory to tackle the vagueness of experts- comments to evaluate the alternatives. Additionally, a modified version of Least-Square method through a non-linear programming model is augmented to the developed group decision making structure in order to elicit the final weights from comparison matrices. Finally, a case study is considered by which developed structure in this paper is validated. Moreover, a sensitivity analysis is performed to validate the response of the model with respect to the condition alteration.

Keywords: Analytic network process, Fuzzy sets theory, Nonlinear programming, Project selection.

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2293 Measuring Banks’ Antifragility via Fuzzy Logic

Authors: Danielle Sandler dos Passos, Helder Coelho, Flávia Mori Sarti

Abstract:

Analysing the world banking sector, we realize that traditional risk measurement methodologies no longer reflect the actual scenario with uncertainty and leave out events that can change the dynamics of markets. Considering this, regulators and financial institutions began to search more realistic models. The aim is to include external influences and interdependencies between agents, to describe and measure the operationalization of these complex systems and their risks in a more coherent and credible way. Within this context, X-Events are more frequent than assumed and, with uncertainties and constant changes, the concept of antifragility starts to gain great prominence in comparison to others methodologies of risk management. It is very useful to analyse whether a system succumbs (fragile), resists (robust) or gets benefits (antifragile) from disorder and stress. Thus, this work proposes the creation of the Banking Antifragility Index (BAI), which is based on the calculation of a triangular fuzzy number – to "quantify" qualitative criteria linked to antifragility.

Keywords: Complex adaptive systems, X-events, risk management, antifragility, banking antifragility index, triangular fuzzy number.

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2292 Fuzzy Logic Control of a Semi-Active Quarter Car System

Authors: Devdutt, M. L. Aggarwal

Abstract:

The development of vehicles having best ride comfort and safety of travelling passengers is of great interest for automotive manufacturers. The effect of transmitted vibrations from car body to passenger seat is required to be controlled for achieving the same. The application of magneto-rheological (MR) shock absorber in suspension system has been considered to achieve significant benefits in this regard. This paper introduces a secondary suspension controlled semi-active quarter car system using MR shock absorber for effective vibration control. Fuzzy logic control system is used for design of controller for actual damping force generation by MR shock absorber. Performance evaluations are done related to passenger seat acceleration and displacement in time and frequency domains, in order to see the effectiveness of the proposed semi-active suspension system. Simulation results show that the semi-active suspension system provides better results compared to passive suspension system in terms of passenger ride comfort improvement.

Keywords: Fuzzy logic control, MR shock absorber, Quarter car model, Semi-active suspension system.

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2291 Optimization of Transportation Cost of Plaster of Paris Cement

Authors: K. M. Oba

Abstract:

The transportation modelling technique was adopted in the solution of the problem of transportation of Plaster of Paris (POP) cement from three supply locations (construction materials markets) to three demand locations (construction sites) in Port Harcourt. The study was carried out for 40 kg bags of POP cement fully loaded on 600 bags per truck from the three selected construction materials markets in Port Harcourt. The costs of transporting the POP cement were determined and subjected to the North-West Corner, Least Cost, and Vogel’s approximation methods to determine the initial feasible solution. Of the three results, the Least Cost Method turned out to have the lowest cost. Using the Stepping Stone Method, the optimum shipping cost was finally attained after two successive iterations. The optimum shipping cost was calculated to be $1,690 or ₦1,774,500 as of October 2023. As a result of this study, the application of transportation modelling can boost the effective management of the transportation of POP cement in construction projects.

Keywords: Cost of POP cement, management of transportation, optimization of shipping cost, Plaster of Paris, transportation model.

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2290 Evaluation of New Product Development Projects using Artificial Intelligence and Fuzzy Logic

Authors: Orhan Feyzioğlu, Gülçin Büyüközkan

Abstract:

As a vital activity for companies, new product development (NPD) is also a very risky process due to the high uncertainty degree encountered at every development stage and the inevitable dependence on how previous steps are successfully accomplished. Hence, there is an apparent need to evaluate new product initiatives systematically and make accurate decisions under uncertainty. Another major concern is the time pressure to launch a significant number of new products to preserve and increase the competitive power of the company. In this work, we propose an integrated decision-making framework based on neural networks and fuzzy logic to make appropriate decisions and accelerate the evaluation process. We are especially interested in the two initial stages where new product ideas are selected (go/no go decision) and the implementation order of the corresponding projects are determined. We show that this two-staged intelligent approach allows practitioners to roughly and quickly separate good and bad product ideas by making use of previous experiences, and then, analyze a more shortened list rigorously.

Keywords: Decision Making, Neural Networks, Fuzzy Theory and Systems, Choquet Integral, New Product Development.

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2289 Optimizing the Project Delivery Time with Time Cost Trade-offs

Authors: Wei Lo, Ming-En Kuo

Abstract:

While to minimize the overall project cost is always one of the objectives of construction managers, to obtain the maximum economic return is definitely one the ultimate goals of the project investors. As there is a trade-off relationship between the project time and cost, and the project delivery time directly affects the timing of economic recovery of an investment project, to provide a method that can quantify the relationship between the project delivery time and cost, and identify the optimal delivery time to maximize economic return has always been the focus of researchers and industrial practitioners. Using genetic algorithms, this study introduces an optimization model that can quantify the relationship between the project delivery time and cost and furthermore, determine the optimal delivery time to maximize the economic return of the project. The results provide objective quantification for accurately evaluating the project delivery time and cost, and facilitate the analysis of the economic return of a project.

Keywords: Time-Cost Trade-Off, Genetic Algorithms, Resource Integration, Economic return.

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2288 Adoption of Appropriate and Cost Effective Technologies in Housing: Indian Experience

Authors: A. K. Jain, M. C. Paliwal

Abstract:

Construction cost in India is increasing at around 50 per cent over the average inflation levels. It have registered increase of up to 15 per cent every year, primarily due to cost of basic building materials such as steel, cement, bricks, timber and other inputs as well as cost of labour. As a result, the cost of construction using conventional building materials and construction is becoming beyond the affordable limits particularly for low-income groups of population as well as a large cross section of the middle - income groups. Therefore, there is a need to adopt cost-effective construction methods either by up-gradation of traditional technologies using local resources or applying modern construction materials and techniques with efficient inputs leading to economic solutions. This has become the most relevant aspect in the context of the large volume of housing to be constructed in both rural and urban areas and the consideration of limitations in the availability of resources such as building materials and finance. This paper makes an overview of the housing status in India and adoption of appropriate and cost effective technologies in the country.

Keywords: Appropriate, Cost Effective, Ekra, Five year plan, Poverty

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2287 A New Approach to Image Segmentation via Fuzzification of Rènyi Entropy of Generalized Distributions

Authors: Samy Sadek, Ayoub Al-Hamadi, Axel Panning, Bernd Michaelis, Usama Sayed

Abstract:

In this paper, we propose a novel approach for image segmentation via fuzzification of Rènyi Entropy of Generalized Distributions (REGD). The fuzzy REGD is used to precisely measure the structural information of image and to locate the optimal threshold desired by segmentation. The proposed approach draws upon the postulation that the optimal threshold concurs with maximum information content of the distribution. The contributions in the paper are as follow: Initially, the fuzzy REGD as a measure of the spatial structure of image is introduced. Then, we propose an efficient entropic segmentation approach using fuzzy REGD. However the proposed approach belongs to entropic segmentation approaches (i.e. these approaches are commonly applied to grayscale images), it is adapted to be viable for segmenting color images. Lastly, diverse experiments on real images that show the superior performance of the proposed method are carried out.

Keywords: Entropy of generalized distributions, entropy fuzzification, entropic image segmentation.

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2286 Enhanced GA-Fuzzy OPF under both Normal and Contingent Operation States

Authors: Ashish Saini, A.K. Saxena

Abstract:

The genetic algorithm (GA) based solution techniques are found suitable for optimization because of their ability of simultaneous multidimensional search. Many GA-variants have been tried in the past to solve optimal power flow (OPF), one of the nonlinear problems of electric power system. The issues like convergence speed and accuracy of the optimal solution obtained after number of generations using GA techniques and handling system constraints in OPF are subjects of discussion. The results obtained for GA-Fuzzy OPF on various power systems have shown faster convergence and lesser generation costs as compared to other approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF) using penalty factors to handle line flow constraints and load bus voltage limits for both normal network and contingency case with congestion. In addition to crossover and mutation rate adaptation scheme that adapts crossover and mutation probabilities for each generation based on fitness values of previous generations, a block swap operator is also incorporated in proposed EGA-OPF. The line flow limits and load bus voltage magnitude limits are handled by incorporating line overflow and load voltage penalty factors respectively in each chromosome fitness function. The effects of different penalty factors settings are also analyzed under contingent state.

Keywords: Contingent operation state, Fuzzy rule base, Genetic Algorithms, Optimal Power Flow.

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2285 Fuzzy Set Approach to Study Appositives and Its Impact Due to Positional Alterations

Authors: E. Mike Dison, T. Pathinathan

Abstract:

Computing with Words (CWW) and Possibilistic Relational Universal Fuzzy (PRUF) are the two concepts which widely represent and measure the vaguely defined natural phenomenon. In this paper, we study the positional alteration of the phrases by which the impact of a natural language proposition gets affected and/or modified. We observe the gradations due to sensitivity/feeling of a statement towards the positional alterations. We derive the classification and modification of the meaning of words due to the positional alteration. We present the results with reference to set theoretic interpretations.

Keywords: Appositive, computing with words, PRUF, semantic sentiment analysis, set theoretic interpretations.

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2284 Towards an Intelligent Ontology Construction Cost Estimation System: Using BIM and New Rules of Measurement Techniques

Authors: F. H. Abanda, B. Kamsu-Foguem, J. H. M. Tah

Abstract:

Construction cost estimation is one of the most important aspects of construction project design. For generations, the process of cost estimating has been manual, time-consuming and error-prone. This has partly led to most cost estimates to be unclear and riddled with inaccuracies that at times lead to over- or underestimation of construction cost. The development of standard set of measurement rules that are understandable by all those involved in a construction project, have not totally solved the challenges. Emerging Building Information Modelling (BIM) technologies can exploit standard measurement methods to automate cost estimation process and improve accuracies. This requires standard measurement methods to be structured in ontological and machine readable format; so that BIM software packages can easily read them. Most standard measurement methods are still text-based in textbooks and require manual editing into tables or Spreadsheet during cost estimation. The aim of this study is to explore the development of an ontology based on New Rules of Measurement (NRM) commonly used in the UK for cost estimation. The methodology adopted is Methontology, one of the most widely used ontology engineering methodologies. The challenges in this exploratory study are also reported and recommendations for future studies proposed.

Keywords: BIM, Construction projects, Cost estimation, NRM, Ontology.

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2283 Clustering Based Formulation for Short Term Load Forecasting

Authors: Ajay Shekhar Pandey, D. Singh, S. K. Sinha

Abstract:

A clustering based technique has been developed and implemented for Short Term Load Forecasting, in this article. Formulation has been done using Mean Absolute Percentage Error (MAPE) as an objective function. Data Matrix and cluster size are optimization variables. Model designed, uses two temperature variables. This is compared with six input Radial Basis Function Neural Network (RBFNN) and Fuzzy Inference Neural Network (FINN) for the data of the same system, for same time period. The fuzzy inference system has the network structure and the training procedure of a neural network which initially creates a rule base from existing historical load data. It is observed that the proposed clustering based model is giving better forecasting accuracy as compared to the other two methods. Test results also indicate that the RBFNN can forecast future loads with accuracy comparable to that of proposed method, where as the training time required in the case of FINN is much less.

Keywords: Load forecasting, clustering, fuzzy inference.

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2282 Performance Evaluation of an ANC-based Hybrid Algorithm for Multi-target Wideband Active Sonar Echolocation System

Authors: Jason Chien-Hsun Tseng

Abstract:

This paper evaluates performances of an adaptive noise cancelling (ANC) based target detection algorithm on a set of real test data supported by the Defense Evaluation Research Agency (DERA UK) for multi-target wideband active sonar echolocation system. The hybrid algorithm proposed is a combination of an adaptive ANC neuro-fuzzy scheme in the first instance and followed by an iterative optimum target motion estimation (TME) scheme. The neuro-fuzzy scheme is based on the adaptive noise cancelling concept with the core processor of ANFIS (adaptive neuro-fuzzy inference system) to provide an effective fine tuned signal. The resultant output is then sent as an input to the optimum TME scheme composed of twogauge trimmed-mean (TM) levelization, discrete wavelet denoising (WDeN), and optimal continuous wavelet transform (CWT) for further denosing and targets identification. Its aim is to recover the contact signals in an effective and efficient manner and then determine the Doppler motion (radial range, velocity and acceleration) at very low signal-to-noise ratio (SNR). Quantitative results have shown that the hybrid algorithm have excellent performance in predicting targets- Doppler motion within various target strength with the maximum false detection of 1.5%.

Keywords: Wideband Active Sonar Echolocation, ANC Neuro-Fuzzy, Wavelet Denoise, CWT, Hybrid Algorithm.

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2281 New Fuzzy Preference Relations and its Application in Group Decision Making

Authors: Nur Syibrah Muhamad Naim, Mohd Lazim Abdullah, Che Mohd Imran Che Taib, Abu OsmanMd. Tap

Abstract:

Decision making preferences to certain criteria usually focus on positive degrees without considering the negative degrees. However, in real life situation, evaluation becomes more comprehensive if negative degrees are considered concurrently. Preference is expected to be more effective when considering both positive and negative degrees of preference to evaluate the best selection. Therefore, the aim of this paper is to propose the conflicting bifuzzy preference relations in group decision making by utilization of a novel score function. The conflicting bifuzzy preference relation is obtained by introducing some modifications on intuitionistic fuzzy preference relations. Releasing the intuitionistic condition by taking into account positive and negative degrees simultaneously and utilizing the novel score function are the main modifications to establish the proposed preference model. The proposed model is tested with a numerical example and proved to be simple and practical. The four-step decision model shows the efficiency of obtaining preference in group decision making.

Keywords: Fuzzy preference relations, score function, conflicting bifuzzy, decision making.

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2280 Combining Fuzzy Logic and Neural Networks in Modeling Landfill Gas Production

Authors: Mohamed Abdallah, Mostafa Warith, Roberto Narbaitz, Emil Petriu, Kevin Kennedy

Abstract:

Heterogeneity of solid waste characteristics as well as the complex processes taking place within the landfill ecosystem motivated the implementation of soft computing methodologies such as artificial neural networks (ANN), fuzzy logic (FL), and their combination. The present work uses a hybrid ANN-FL model that employs knowledge-based FL to describe the process qualitatively and implements the learning algorithm of ANN to optimize model parameters. The model was developed to simulate and predict the landfill gas production at a given time based on operational parameters. The experimental data used were compiled from lab-scale experiment that involved various operating scenarios. The developed model was validated and statistically analyzed using F-test, linear regression between actual and predicted data, and mean squared error measures. Overall, the simulated landfill gas production rates demonstrated reasonable agreement with actual data. The discussion focused on the effect of the size of training datasets and number of training epochs.

Keywords: Adaptive neural fuzzy inference system (ANFIS), gas production, landfill

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