05811nam 2200433 450 991063392710332120231110225006.03-031-16832-1(MiAaPQ)EBC7152388(Au-PeEL)EBL7152388(CKB)25607670200041(EXLCZ)992560767020004120230414d2023 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierEngineering applications of modern metaheuristics /edited by Taymaz Akan [and three others]Cham, Switzerland :Springer,[2023]©20231 online resource (209 pages)Studies in Computational Intelligence ;v.1069Print version: Akan, Taymaz Engineering Applications of Modern Metaheuristics Cham : Springer International Publishing AG,c2023 9783031168314 Intro -- Contents -- Empirical Comparison of Heuristic Optimisation Methods for Automated Car Setup -- 1 Introduction -- 2 The Open Racing Car Simulator (TORCS) -- 3 Heuristics, Metaheuristics and Hyper-Heuristics -- 3.1 Selection Hyper-Heuristics -- 3.2 Covariance Matrix Adaptation Evolutionary Strategy -- 3.3 Closest Best Closest Worst Particle Swarm Optimisation -- 4 Experimental Design -- 5 Results and Discussion -- 5.1 Comparison of Heuristic Selection Methods -- 5.2 Comparison of Individual Low Level Heuristics -- 5.3 Comparison with Other Methods -- 6 Conclusion -- References -- Metaheuristic Algorithms in IoT: Optimized Edge Node Localization -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 The Grey Wolf Optimizer (GWO) -- 3.2 Moth-Flame Optimization (MFO) -- 3.3 Hybrid Algorithm (GWOMFO) -- 4 Results Analysis -- 4.1 Benchmark Functions (CEC2015) -- 4.2 Benchmark Functions (CEC2019) -- 4.3 Edge Node Localization Problem -- 5 Conclusion -- References -- JAYA Algorithm Versus Differential Evolution: A Comparative Case Study on Optic Disc Localization in Eye Fundus Images -- 1 Introduction -- 2 JAYA Algorithm for Optic Disc Localization -- 2.1 Fitness Evaluation -- 3 Performance Analysis -- 4 Conclusion -- References -- Minimum Transmission Power Control for the Internet of Things with Swarm Intelligence Algorithms -- 1 Introduction -- 1.1 Main Contributions of the Study -- 2 Literature Review -- 3 Material and Methods -- 3.1 Minimum Transmission Power Control -- 3.2 Particle Swarm Optimization (PSO) -- 3.3 Artificial Bee Colony (ABC) -- 3.4 Salp Swarm Algorithm (SSA) -- 3.5 Tree-Seed Algorithm (TSA) -- 4 Experimental Setup -- 5 Results and Discussions -- 6 Conclusion -- References -- An Enhanced Gradient Based Optimized Controller for Load Frequency Control of a Two Area Automatic Generation Control System -- 1 Introduction.2 Mathematical Model of the System -- 2.1 Governor Model -- 2.2 Turbine Model -- 2.3 Generator-Load Model -- 2.4 Tie-Line -- 3 Optimization Techniques -- 3.1 Gradient-Based Optimizer -- 3.2 Enhanced Gradient-Based Optimizer -- 4 Controller Structure with Problem Formulation -- 5 Study Results and Discussions -- 5.1 Case Studies -- 5.2 Convergence Comparison of the Optimizers -- 5.3 Comparative Statistical Analysis -- 6 Conclusion -- Appendix A -- Appendix B -- Appendix C -- Appendix D -- References -- A Meta-Heuristic Algorithm Based on the Happiness Model -- 1 Introduction -- 2 Happiness Optimizer -- 2.1 Inspiration -- 3 Comparative Study -- 3.1 Statistical Discussion -- 3.2 Real Problem -- 4 Conclusions -- References -- Application of Metaheuristic Techniques for Enhancing the Financial Profitability of Wind Power Generation Systems -- 1 Introduction -- 2 Objective Formulation -- 2.1 Annual Profit Calculation -- 2.2 Wind Flow Pattern -- 2.3 Terrain Conditions -- 3 Optimization Algorithms -- 3.1 Binary Particle Swarm Optimization Algorithm (BPSOA) -- 3.2 Genetic Algorithm (GA) -- 3.3 Proposed Enhanced GA -- 4 Results and Discussion -- 5 Conclusion -- References -- Optimization of Demand Response -- 1 Introduction -- 2 Demand Response -- 3 Loads -- 4 Renewable Energy Sources and Storage Systems -- 4.1 Renewable Energy Sources -- 4.2 Storage Systems -- 5 Tariff -- 6 User Comfort -- 7 Problem Formulation -- 8 Optimization Techniques -- References -- Fitting Curves of Ruminal Degradation Using a Metaheuristic Approach -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Collection -- 2.2 Particle Swarm Optimization (PSO) -- 2.3 Curve Fitting -- 3 Proposed Algorithm -- 3.1 Fitness Function -- 4 Results and Discussion -- 5 Conclusions -- References -- Optimizing a Real Case Assembly Line Balancing Problem Using Various Techniques -- 1 Introduction.2 Literature Review -- 3 Problem Definition and Formulation -- 4 Methodology -- 5 Computational Results -- 5.1 Straight Line -- 5.2 U-Shaped Line -- 6 Conclusion -- References -- Multi-circle Detection Using Multimodal Optimization -- 1 Introduction -- 2 Particle Swarm Optimization -- 2.1 Multimodal PSO -- 2.2 Local Search PSO -- 3 Proposed Method -- 4 Experimental Results -- 4.1 EPSO Based Multiple Circle Detection Application Results -- 4.2 EPSO Based Multiple Circle Detection Application Performance Results -- 4.3 Comparison of Standard Hough Transform with EPSO Based Multiple Circle Detection -- 5 Conclusions -- References.Studies in Computational Intelligence Computer scienceMathematicsComputer scienceMathematics.215Akan TaymazMiAaPQMiAaPQMiAaPQBOOK9910633927103321Engineering applications of modern metaheuristics3089260UNINA