Metaheuristic computation. ([2021])

• Record Type: Book
• Further Information: Note: Erik Cuevas, Primitivo Diaz, Octavio Camarena.
• Authors: Cuevas, Erik; Diaz, Primitivo; Camarena, Octavio
• Contents: Intro -- Preface -- Contents -- 1 Introductory Concepts of Metaheuristic Computation -- 1.1 Formulation of an Optimization Problem -- 1.2 Classical Optimization Methods -- 1.3 Metaheuristic Computation Schemes -- 1.3.1 Generic Structure of a Metaheuristic Method -- References -- 2 An Enhanced Swarm Method Based on the Locust Search Algorithm -- 2.1 Introduction -- 2.2 The Locust Search Algorithm -- 2.2.1 LS Solitary Phase -- 2.2.2 LS Social Phase -- 2.3 The LS-II Algorithm -- 2.3.1 Selecting Between Solitary and Social Phases -- 2.3.2 Modified Social Phase Operator 2.4 Experiments and Results -- 2.4.1 Benchmark Test Functions -- 2.4.2 Engineering Optimization Problems -- 2.5 Conclusions -- Appendix A -- Appendix B -- B2.1 Pressure Vessel Design Problem -- B2.2 Gear Train Design Problem -- B2.3 Tension/Compression Spring Design Problem -- B2.4 Three-Bar Truss Design Problem -- B2.5 Welded Beam Design Problem -- B2.6. Parameter Estimation for FM Synthesizers -- B2.7 Optimal Capacitor Placement for the IEEE's 69-Bus Radial Distribution Networks -- References -- 3 A Metaheuristic Methodology Based on Fuzzy Logic Principles -- 3.1 Introduction 3.2 Fuzzy Logic and Reasoning Models -- 3.2.1 Fuzzy Logic Concepts -- 3.2.2 The Takagi-Sugeno (TS) Fuzzy Model -- 3.3 The Proposed Methodology -- 3.3.1 Optimization Strategy -- 3.3.2 Computational Procedure -- 3.4 Discussion About the Proposed Methodology -- 3.4.1 Optimization Algorithm -- 3.4.2 Modeling Characteristics -- 3.5 Experimental Study -- 3.5.1 Performance Evaluation with Regard to Its Own Tuning Parameters -- 3.5.2 Comparison with Other Optimization Approaches -- 3.6 Conclusions -- Appendix A. List of Benchmark Functions -- References 4 A Metaheuristic Computation Scheme to Solve Energy Problems -- 4.1 Introduction -- 4.2 Crow Search Algorithm (CSA) -- 4.3 The Proposed Improved Crow Search Algorithm (ICSA) -- 4.3.1 Dynamic Awareness Probability (DAP) -- 4.3.2 Random Movement-Lévy Flight -- 4.4 Motor Parameter Estimation Formulation -- 4.4.1 Approximate Circuit Model -- 4.4.2 Exact Circuit Model -- 4.5 Capacitor Allocation Problem Formulation -- 4.5.1 Load Flow Analysis -- 4.5.2 Mathematical Approach -- 4.5.3 Sensitivity Analysis and Loss Sensitivity Factor -- 4.6 Experiments -- 4.6.1 Motor Parameter Estimation Test 4.6.2 Capacitor Allocation Test -- 4.7 Conclusions -- Appendix A: Systems Data -- References -- 5 ANFIS-Hammerstein Model for Nonlinear Systems Identification Using GSA -- 5.1 Introduction -- 5.2 Background -- 5.2.1 Hybrid ANFIS Models -- 5.2.2 Adaptive Neuro-Fuzzy Inference System (ANFIS) -- 5.2.3 Gravitational Search Algorithm (GSA) -- 5.3 Hammerstein Model Identification by Using GSA -- 5.4 Experimental Study -- 5.4.1 Experiment I -- 5.4.2 Experiment II -- 5.4.3 Experiment III -- 5.4.4 Experiment IV -- 5.4.5 Experiment V -- 5.4.6 Experiment VI -- 5.4.7 Experiment VII -- a5.4.8 Statistical Analysis.
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2021
• Extent: 1 online resource (281 pages)
• Subjects: 005.1; Metaheuristics; Electronic books
• Languages: English
• ISBNs: 9783030581008; 3030581004
• Related ISBNs: 3030580997; 9783030580995
• Notes: Note: Includes bibliographical references.; Note: Description based on online resource; title from digital title page (viewed on December 11, 2020).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.