Swarm, Evolutionary, and Memetic Computing [[electronic resource] ] : 6th International Conference, SEMCCO 2015, Hyderabad, India, December 18-19, 2015, Revised Selected Papers / / edited by Bijaya Ketan Panigrahi, Ponnuthurai Nagaratnam Suganthan, Swagatam Das, Suresh Chandra Satapathy

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
• Edizione: 1st ed. 2016.
• Descrizione fisica: 1 online resource (XI, 288 p. 117 illus.)
• Disciplina: 006.3
• Soggetto topico: Computer science; Artificial intelligence; Algorithms; Pattern recognition systems; Computer networks; Software engineering; Theory of Computation; Artificial Intelligence; Automated Pattern Recognition; Computer Communication Networks; Software Engineering
• Persona (resp. second.): PanigrahiBijaya Ketan; SuganthanPonnuthurai Nagaratnam; DasSwagatam; SatapathySuresh Chandra
• Nota di contenuto: Intro -- Preface -- Organization -- Contents -- Self-adaptive Ensemble Differential Evolution with Sampled Parameter Values for Unit Commitment -- Abstract -- 1 Introduction -- 2 Literature Review -- 2.1 Differential Evolution -- 2.2 Literature Review -- 3 Self-adaptive DE with Ensemble of Mutation Strategies and Sampled Parameter Values (Sa-EPSDE) -- 4 Experimental Study on Numerical Benchmark Problems -- 5 Experimental Study on Unit Commitment Problem -- 5.1 Problem Formulation -- 5.2 Simple Priority Listing Method -- 5.3 Experimental Results -- 6 Conclusion -- Acknowledgement -- References -- Empirical Assessment of Human Learning Principles Inspired PSO Algorithms on Continuous Black-Box Optimization Testbed -- 1 Introduction -- 2 Selected Human Learning Principles Inspired PSO Algorithms -- 3 Numerical Assessment -- 3.1 Setup -- 3.2 Performance Evaluation Procedure -- 3.3 Performance Evaluation Discussion -- 4 Conclusion -- References -- Visual Cryptography Based Lossless Watermarking for Sensitive Images -- Abstract -- 1 Introduction -- 2 Visual Cryptography Based Lossless Watermarking (VCLW) -- 3 Spatial Domain VCLW Techniques -- 4 Results and Discussion -- 5 Conclusions -- References -- Cohort Intelligence and Genetic Algorithm Along with AHP to Recommend an Ice Cream to a Diabetic Patient -- Abstract -- 1 Introduction -- 2 AHP Matrix Methodology -- 3 Proposed AHP-GA Algorithm -- 3.1 Proposed Set of Equations for Different Variables -- 3.2 Selection Criteria for AHP-GA -- 3.3 Fitness Function and Recommending an Ice Cream to Diabetic Patients -- 4 AHP-CI Algorithm -- 5 Conclusions and Future Direction -- References -- Design, Construction and Analysis of Model Dataset for Indian Road Network and Performing Classification to Estimate Accuracy of Different Classifier with Its Comparison Summary Evaluation -- Abstract -- 1 Introduction. ; 2 Related Work -- 3 Performing Analysis of Data and Setting Threshold Levels -- 4 Database Creation -- 5 Testing Data with Different Algorithm and Accuracy Estimation -- 5.1 System Architecture -- 5.2 Final Evaluation Summary -- 6 Conclusion and Future Work -- References -- A Hybrid EMD-ANN Model for Stock Price Prediction -- 1 Introduction -- 2 Hybrid EMD-ANN Framework -- 2.1 Steps of EMD -- 2.2 Steps of ANN -- 3 Analysis -- 3.1 Data Description -- 3.2 EMD -- 3.3 Box-Jenkins Methodology -- 3.4 ANN -- 4 Results and Discussion -- 4.1 Error Measures -- 4.2 Significance Test -- 5 Conclusion -- References -- Development of Back Propagation Neural Network (BPNN) Model to Predict Combustion Parameters of Diesel Engine -- Abstract -- 1 Introduction -- 2 Experimental Setup -- 2.1 Experiment Procedure -- 3 Results and Discussions -- 4 Conclusions -- References -- An Improved Quantum Inspired Immune Clone Optimization Algorithm -- 1 Introduction -- 2 Related Methods -- 2.1 Immune Clone Algorithm -- 2.2 Quantum Computing Theory -- 3 Proposed Approach -- 3.1 Quantum Immune Clone Algorithm -- 3.2 An Improved Quantum Immune Clone Algorithm: Proposed Algorithm -- 4 Results and Discussions -- 5 Conclusion and Future Work -- References -- Diagnosis of Parkinson Disease Patients Using Egyptian Vulture Optimization Algorithm -- 1 Inroduction -- 1.1 Existing Method for Diagnosis of PD -- 1.2 Need for Feature Selection -- 2 Methodology -- 2.1 KNN Classifier -- 2.2 Particle Swarm Optimization -- 2.3 Egyptian Vulture Optimization Algorithm -- 2.4 Pebble Tossing -- 2.5 Rolling with Twigs -- 2.6 Change of Angle -- 2.7 Fitness Calculation -- 3 Experimental Results -- References -- Variance Based Particle Swarm Optimization for Function Optimization and Feature Selection -- 1 Introduction -- 2 Particle Swarm Optimization -- 2.1 Binary PSO -- 2.2 BPSO for Feature Selection. ; 3 Proposed Variance Based Particle Swarm Optimization -- 3.1 VPSO Algorithm -- 3.2 Time Complexity -- 4 Experiments -- 4.1 Function Minimization -- 4.2 Application of VPSO for Feature Selection -- 5 Conclusion and Future Work -- References -- Analysis of Next-Generation Sequencing Data of miRNA for the Prediction of Breast Cancer -- 1 Introduction -- 2 Gravitation Search Algorithm Integrated Support Vector Machine -- 2.1 Population Initialization -- 2.2 Fitness Computation -- 2.3 Mass and Gravitational Force Computation -- 2.4 Updating Velocity and Position -- 2.5 Elitism -- 2.6 Ranking of miRNAs Selected by GSA+SVM -- 3 Experimental Results -- 3.1 Dataset -- 3.2 Parameters Settings and Performance Metrics -- 3.3 Results -- 4 Conclusion -- References -- Genetic Algorithm Based Speed Control of Electric Vehicle with Electronic Differential -- Abstract -- 1 Introduction -- 2 Mathematical Model of PMSM -- 2.1 Three Phase to Two Phase Transformation -- 3 Vector Control of PMSM -- 4 Modeling of Electronic Differential Controller -- 5 Optimal Tuning of PI Controller Using Genetic Algorithm -- 6 Objective Function -- 7 Result and Discussion -- 7.1 Varying Speed and Varying Load -- 7.2 Case A: Vehicle Moving on Left Curved Road -- 7.3 Case B:Vehicle Moving on a Right Curved Road -- A Appendix: Motor Parameters -- References -- An Ant Colony Optimization Approach for the Dominating Tree Problem -- 1 Introduction -- 2 Related Work -- 3 DT-ACO -- 3.1 Solution Construction -- 4 Computational Results -- 4.1 Parameter Settings -- 4.2 Comparison of DT-ACO with ACO and ABC -- 5 Conclusions -- References -- Multi-objective Power Dispatch Using Stochastic Fractal Search Algorithm and TOPSIS -- Abstract -- 1 Introduction -- 2 Mathematical Formulation -- 2.1 Cost Function for Economic Dispatch Problem -- 2.2 Function for Emission Dispatch. ; 2.3 Power Balance Constraints -- 2.4 Generation Limits Constraints -- 2.5 Formulation of Economic Emission Dispatch Problem -- 3 Stochastic Fractal Search Algorithm -- 3.1 Diffusion Process -- 3.2 Updating Process -- 4 TOPSIS -- 5 Implementation of SFSA in Economic Emission Dispatch Problem -- 6 Simulation Results -- 6.1 Test Case 1: 10 Unit System -- 6.2 Test Case 2: 13unit System -- 7 Conclusion -- References -- Particle Swarm Optimization for the Deployment of Directional Sensors -- 1 Introduction -- 2 Related Work -- 3 Problem Definition -- 4 Proposed Approach -- 5 Results and Discussion -- 6 Conclusion and Future Work -- References -- Region Based Multiple Features for an Effective Content Based Access Medical Image Retrieval an Integrated with Relevance Feedback Approach -- Abstract -- 1 Introduction -- 2 CBMIR System -- 3 Feature Extraction Approach -- 3.1 Boundary Detection -- 3.2 Texture Pattern Extraction -- 3.3 Shape Feature Extraction -- 4 Relevance Feedback Learning Approach -- 5 Experimental Results -- 6 Discussion and Conclusion -- References -- Robot Workcell Layout Optimization Using Firefly Algorithm -- Abstract -- 1 Introduction -- 2 Methodology -- 2.1 B-Star Tree Representation -- 2.2 Sequence Pair Representation -- 2.3 Objective Function -- 3 The Firefly Algorithm -- 4 Results and Discussion -- 5 Conclusion -- Acknowledgment -- References -- Particle Swarm Optimization Based on the Winner's Strategy -- Abstract -- 1 Introduction -- 2 PSO with Winners Strategy -- 2.1 Discussion on Selection of Value of Φ -- 2.2 Discussion on New Velocity Update Formula -- 3 Experimental Results and Analysis -- 4 Conclusion and Future Work -- Appendix -- References -- Black Hole Artificial Bee Colony Algorithm -- 1 Introduction -- 2 Black Hole Phenomenon -- 3 Black Hole ABC Algorithm -- 4 Outcomes and Discussions -- 5 Conclusion -- References. ; A Gravitational Search Algorithm for Energy Efficient Multi-sink Placement in Wireless Sensor Networks -- Abstract -- 1 Introduction -- 2 Reviews of Literature -- 3 Preliminaries -- 3.1 Gravitational Search Algorithm -- 3.2 Energy Model -- 3.3 Network Scenario and Notations -- 3.3.1 Network Scenario -- 3.3.2 Notations -- 4 Proposed Approach -- 4.1 Representation of an Agent -- 4.2 Derivation of Fitness Function -- 4.3 Updating of Velocity and Position -- 5 Simulation Results -- 6 Conclusion -- References -- Optimum Clustering of Active Distribution Networks Using Back Tracking Search Algorithm -- Abstract -- 1 Introduction -- 2 Microgrids Design Concept and Benefits -- 3 Modeling of System Components -- 4 Problem Formulation -- 4.1 First Objective -- 4.2 Second Objective -- 5 The Solution Algorithm -- 5.1 Initialization -- 5.2 Selection-I -- 5.3 Mutation -- 5.4 Crossover -- 5.5 Selection-II -- 6 Simulation Results -- 7 Conclusions -- References -- Energy Efficient Clustering for Wireless Sensor Networks: A Gravitational Search Algorithm -- Abstract -- 1 Introduction -- 2 Preliminaries -- 2.1 Overview of Gravitational Search Algorithm -- 2.2 Energy Model -- 2.3 WSN Model and Notations -- 2.3.1 WSN Model -- 2.3.2 Notations -- 3 Proposed Approach -- 3.1 Initialization and Representation of Agent -- 3.2 Derivation of Fitness Function -- 3.3 Illustration -- 4 Simulation Results -- 5 Conclusion and Future Work -- References -- Hybridizing Cuckoo Search with Bio-inspired Algorithms for Constrained Optimization Problems -- Abstract -- 1 Introduction -- 2 Cuckoo Search Algorithm -- 2.1 Lévy Flight -- 2.2 Hybrid CS-GA Algorithm -- 2.3 Hybrid CS-PSO Algorithm -- 3 Test Problems and Results -- 3.1 Himmelblau's Problem -- 3.2 Cantilever Beam Design Problem -- 3.3 Tubular Column Design Problem -- 3.4 Three Bar Truss Design Problem. ; 3.5 Corrugated Bulkhead Design Problem.
• Sommario/riassunto: This volume constitutes the thoroughly refereed post-conference proceedings of the 6th International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2015, held in Hyderabad, India, in December 2015. The 23 full papers presented in this volume were carefully reviewed and selected from 40 submissions for inclusion in the proceedings. The papers cover a wide range of topics in swarm, evolutionary, memetic and other intelligent computing algorithms and their real world applications in problems selected from diverse domains of science and engineering.
• Titolo autorizzato: Swarm, Evolutionary, and Memetic Computing
• ISBN: 3-319-48959-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996465599703316
• Lo trovi qui: Univ. di Salerno
• Serie: Theoretical Computer Science and General Issues, . 2512-2029 ; ; 9873