Search results for: Fuzzy Programming
733 Parallezation Protein Sequence Similarity Algorithms using Remote Method Interface
Authors: Mubarak Saif Mohsen, Zurinahni Zainol, Rosalina Abdul Salam, Wahidah Husain
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One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.
Keywords: Protein sequence algorithm, dynamic programming algorithm, multithread
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1888732 Automatic Detection of Proliferative Cells in Immunohistochemically Images of Meningioma Using Fuzzy C-Means Clustering and HSV Color Space
Authors: Vahid Anari, Mina Bakhshi
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 669731 On the Application of Meta-Design Techniques in Hardware Design Domain
Authors: R. Damaševičius
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System-level design based on high-level abstractions is becoming increasingly important in hardware and embedded system design. This paper analyzes meta-design techniques oriented at developing meta-programs and meta-models for well-understood domains. Meta-design techniques include meta-programming and meta-modeling. At the programming level of design process, metadesign means developing generic components that are usable in a wider context of application than original domain components. At the modeling level, meta-design means developing design patterns that describe general solutions to the common recurring design problems, and meta-models that describe the relationship between different types of design models and abstractions. The paper describes and evaluates the implementation of meta-design in hardware design domain using object-oriented and meta-programming techniques. The presented ideas are illustrated with a case study.Keywords: Design patterns, meta-design, meta-modeling, metaprogramming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2292730 A New Framework for Evaluation and Prioritization of Suppliers using a Hierarchical Fuzzy TOPSIS
Authors: Mohammad Taghi Taghavifard, Danial Mirheydari
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1394729 Monte Carlo Analysis and Fuzzy Sets for Uncertainty Propagation in SIS Performance Assessment
Authors: Fares Innal, Yves Dutuit, Mourad Chebila
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2768728 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3210727 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1928726 Using Data Mining for Learning and Clustering FCM
Authors: Somayeh Alizadeh, Mehdi Ghazanfari, Mohammad Fathian
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2003725 Fuzzy Group Decision Making for the Assessment of Health-Care Waste Disposal Alternatives in Istanbul
Authors: Mehtap Dursun, E. Ertugrul Karsak, Melis Almula Karadayi
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1676724 A Cascaded Fuzzy Inference System for Dynamic Online Portals Customization
Authors: Erika Martinez Ramirez, Rene V. Mayorga
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1776723 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1893722 Artificial Neural Network Development by means of Genetic Programming with Graph Codification
Authors: Daniel Rivero, Julián Dorado, Juan R. Rabuñal, Alejandro Pazos, Javier Pereira
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The development of Artificial Neural Networks (ANNs) is usually a slow process in which the human expert has to test several architectures until he finds the one that achieves best results to solve a certain problem. This work presents a new technique that uses Genetic Programming (GP) for automatically generating ANNs. To do this, the GP algorithm had to be changed in order to work with graph structures, so ANNs can be developed. This technique also allows the obtaining of simplified networks that solve the problem with a small group of neurons. In order to measure the performance of the system and to compare the results with other ANN development methods by means of Evolutionary Computation (EC) techniques, several tests were performed with problems based on some of the most used test databases. The results of those comparisons show that the system achieves good results comparable with the already existing techniques and, in most of the cases, they worked better than those techniques.Keywords: Artificial Neural Networks, Evolutionary Computation, Genetic Programming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1448721 Genetic Programming Based Data Projections for Classification Tasks
Authors: César Estébanez, Ricardo Aler, José M. Valls
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In this paper we present a GP-based method for automatically evolve projections, so that data can be more easily classified in the projected spaces. At the same time, our approach can reduce dimensionality by constructing more relevant attributes. Fitness of each projection measures how easy is to classify the dataset after applying the projection. This is quickly computed by a Simple Linear Perceptron. We have tested our approach in three domains. The experiments show that it obtains good results, compared to other Machine Learning approaches, while reducing dimensionality in many cases.
Keywords: Classification, genetic programming, projections.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1385720 Measuring Banks’ Antifragility via Fuzzy Logic
Authors: Danielle Sandler dos Passos, Helder Coelho, Flávia Mori Sarti
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 868719 A Fuzzy Satisfactory Optimization Method Based on Stress Analysis for a Hybrid Composite Flywheel
Authors: Liping Yang, Curran Crawford, Jr. Ren, Zhengyi Ren
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Considering the cost evaluation and the stress analysis, a fuzzy satisfactory optimization (FSO) method has been developed for a hybrid composite flywheel. To evaluate the cost, the cost coefficients of the flywheel components are obtained through calculating the weighted sum of the scores of the material manufacturability, the structure character, and the material price. To express the satisfactory degree of the energy, the cost, and the mass, the satisfactory functions are proposed by using the decline function and introducing a satisfactory coefficient. To imply the different significance of the objectives, the object weight coefficients are defined. Based on the stress analysis of composite material, the circumferential and radial stresses are considered into the optimization formulation. The simulations of the FSO method with different weight coefficients and storage energy density optimization (SEDO) method of a flywheel are contrasted. The analysis results show that the FSO method can satisfy different requirements of the designer and the FSO method with suitable weight coefficients can replace the SEDO method.
Keywords: Flywheel energy storage, fuzzy, optimization, stress analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 950718 Fuzzy Logic Control of a Semi-Active Quarter Car System
Authors: Devdutt, M. L. Aggarwal
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3132717 Evaluation of New Product Development Projects using Artificial Intelligence and Fuzzy Logic
Authors: Orhan Feyzioğlu, Gülçin Büyüközkan
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2821716 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3216715 Using the PGAS Programming Paradigm for Biological Sequence Alignment on a Chip Multi-Threading Architecture
Authors: M. Bakhouya, S. A. Bahra, T. El-Ghazawi
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The Partitioned Global Address Space (PGAS) programming paradigm offers ease-of-use in expressing parallelism through a global shared address space while emphasizing performance by providing locality awareness through the partitioning of this address space. Therefore, the interest in PGAS programming languages is growing and many new languages have emerged and are becoming ubiquitously available on nearly all modern parallel architectures. Recently, new parallel machines with multiple cores are designed for targeting high performance applications. Most of the efforts have gone into benchmarking but there are a few examples of real high performance applications running on multicore machines. In this paper, we present and evaluate a parallelization technique for implementing a local DNA sequence alignment algorithm using a PGAS based language, UPC (Unified Parallel C) on a chip multithreading architecture, the UltraSPARC T1.Keywords: Partitioned Global Address Space, Unified Parallel C, Multicore machines, Multi-threading Architecture, Sequence alignment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1380714 Defining Programming Problems as Learning Objects
Authors: José Paulo Leal, Ricardo Queirós
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Standards for learning objects focus primarily on content presentation. They were already extended to support automatic evaluation but it is limited to exercises with a predefined set of answers. The existing standards lack the metadata required by specialized evaluators to handle types of exercises with an indefinite set of solutions. To address this issue existing learning object standards were extended to the particular requirements of a specialized domain. A definition of programming problems as learning objects, compatible both with Learning Management Systems and with systems performing automatic evaluation of programs, is presented in this paper. The proposed definition includes metadata that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements of the evaluation engine; and the roles of different assets - tests cases, program solutions, etc. The EduJudge project and its main services are also presented as a case study on the use of the proposed definition of programming problems as learning objects.Keywords: Content Packaging, eLearning Services, Interoperability, Learning Objects.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1542713 Optimal Choice and Location of Multi Type Facts Devices in Deregulated Electricity Market Using Evolutionary Programming Method
Authors: K. Balamurugan, R. Muralisachithanandam, V. Dharmalingam, R. Srikanth
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This paper deals with the optimal choice and allocation of multi FACTS devices in Deregulated power system using Evolutionary Programming method. The objective is to achieve the power system economic generation allocation and dispatch in deregulated electricity market. Using the proposed method, the locations of the FACTS devices, their types and ratings are optimized simultaneously. Different kinds of FACTS devices are simulated in this study such as UPFC, TCSC, TCPST, and SVC. Simulation results validate the capability of this new approach in minimizing the overall system cost function, which includes the investment costs of the FACTS devices and the bid offers of the market participants. The proposed algorithm is an effective and practical method for the choice and allocation of FACTS devices in deregulated electricity market environment. The standard data of IEEE 14 Bus systems has been taken into account and simulated with aid of MAT-lab software and results were obtained.
Keywords: FACTS devices, Optimal allocation, Deregulated electricity market, Evolutionary programming, Mat Lab.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2299712 A Robust Optimization Model for the Single-Depot Capacitated Location-Routing Problem
Authors: Abdolsalam Ghaderi
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In this paper, the single-depot capacitated location-routing problem under uncertainty is presented. The problem aims to find the optimal location of a single depot and the routing of vehicles to serve the customers when the parameters may change under different circumstances. This problem has many applications, especially in the area of supply chain management and distribution systems. To get closer to real-world situations, travel time of vehicles, the fixed cost of vehicles usage and customers’ demand are considered as a source of uncertainty. A combined approach including robust optimization and stochastic programming was presented to deal with the uncertainty in the problem at hand. For this purpose, a mixed integer programming model is developed and a heuristic algorithm based on Variable Neighborhood Search(VNS) is presented to solve the model. Finally, the computational results are presented and future research directions are discussed.Keywords: Location-routing problem, robust optimization, Stochastic Programming, variable neighborhood search.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 742711 Enhanced GA-Fuzzy OPF under both Normal and Contingent Operation States
Authors: Ashish Saini, A.K. Saxena
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1602710 Fuzzy Set Approach to Study Appositives and Its Impact Due to Positional Alterations
Authors: E. Mike Dison, T. Pathinathan
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 825709 Lifetime Maximization in Wireless Ad Hoc Networks with Network Coding and Matrix Game
Authors: Jain-Shing Liu
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In this paper, we present a matrix game-theoretic cross-layer optimization formulation to maximize the network lifetime in wireless ad hoc networks with network coding. To this end, we introduce a cross-layer formulation of general NUM (network utility maximization) that accommodates routing, scheduling, and stream control from different layers in the coded networks. Specifically, for the scheduling problem and then the objective function involved, we develop a matrix game with the strategy sets of the players corresponding to hyperlinks and transmission modes, and design the payoffs specific to the lifetime. In particular, with the inherit merit that matrix game can be solved with linear programming, our cross-layer programming formulation can benefit from both game-based and NUM-based approaches at the same time by cooperating the programming model for the matrix game with that for the other layers in a consistent framework. Finally, our numerical example demonstrates its performance results on a well-known wireless butterfly network to verify the cross-layer optimization scheme.Keywords: Cross-layer design, Lifetime maximization, Matrix game, Network coding
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1684708 Predicting the Minimum Free Energy RNA Secondary Structures using Harmony Search Algorithm
Authors: Abdulqader M. Mohsen, Ahamad Tajudin Khader, Dhanesh Ramachandram, Abdullatif Ghallab
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The physical methods for RNA secondary structure prediction are time consuming and expensive, thus methods for computational prediction will be a proper alternative. Various algorithms have been used for RNA structure prediction including dynamic programming and metaheuristic algorithms. Musician's behaviorinspired harmony search is a recently developed metaheuristic algorithm which has been successful in a wide variety of complex optimization problems. This paper proposes a harmony search algorithm (HSRNAFold) to find RNA secondary structure with minimum free energy and similar to the native structure. HSRNAFold is compared with dynamic programming benchmark mfold and metaheuristic algorithms (RnaPredict, SetPSO and HelixPSO). The results showed that HSRNAFold is comparable to mfold and better than metaheuristics in finding the minimum free energies and the number of correct base pairs.
Keywords: Metaheuristic algorithms, dynamic programming algorithms, harmony search optimization, RNA folding, Minimum free energy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2319707 Clustering Based Formulation for Short Term Load Forecasting
Authors: Ajay Shekhar Pandey, D. Singh, S. K. Sinha
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1608706 Performance Evaluation of an ANC-based Hybrid Algorithm for Multi-target Wideband Active Sonar Echolocation System
Authors: Jason Chien-Hsun Tseng
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2043705 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1415704 Study on Optimal Control Strategy of PM2.5 in Wuhan, China
Authors: Qiuling Xie, Shanliang Zhu, Zongdi Sun
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In this paper, we analyzed the correlation relationship among PM2.5 from other five Air Quality Indices (AQIs) based on the grey relational degree, and built a multivariate nonlinear regression equation model of PM2.5 and the five monitoring indexes. For the optimal control problem of PM2.5, we took the partial large Cauchy distribution of membership equation as satisfaction function. We established a nonlinear programming model with the goal of maximum performance to price ratio. And the optimal control scheme is given.
Keywords: Grey relational degree, multiple linear regression, membership function, nonlinear programming.
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