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020 _a9783030264581
024 7 _a10.1007/978-3-030-26458-1
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQA76.9 .N38
_b2020 EB
245 0 0 _aNature-Inspired Methods for Metaheuristics Optimization :
_bAlgorithms and Applications in Science and Engineering
_cedited by Fouad Bennis, Rajib Kumar Bhattacharjya
250 _aPrimera edición 2020
264 1 _aCham
_bSpringer
_c2020
300 _a1 recurso en línea (XIII, 502 páginas)
_b 252 ilustraciones, 110 ilustraciones a color.
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _atext file
_bPDF
490 0 _aModeling and Optimization in Science and Technologies
_x2196-7326
_v16
490 0 _aEngineering (Springer-11647)
505 0 _aPart I. Algorithms: 1. Genetic algorithms: A mature bio-inspired optimization technique for difficult problems -- 2. Introduction to Genetic Algorithm with a Simple Analogy -- 3. Interactive genetic algorithm to collect user perceptions. Application to the design of stemmed glasses -- 4. Differential Evolution and its application in Identification of Virus Release Location in a Sewer Line -- 5. Artificial Bee Colony Algorithm and An Application to Software Defect Prediction -- 6. Firefly Algorithm and its Applications in Engineering Optimization -- 7. Introduction to Shuffled Frog Leaping Algorithm and its Sensitivity to the Parameters of the Algorithm -- 8. Groundwater Management using Coupled Analytic Element based Transient Groundwater Flow and Optimization Model -- 9. Investigation of Bacterial Foraging Algorithm applied for PV parameter estimation, Selective harmonic elimination in inverters and optimal power flow for stability -- 10. Application of artificial immune system in Optimal Design of Irrigation Canal -- 11. Biogeography Based Optimization for Water Pump Switching Problem -- 12. Introduction to Invasive Weed Optimization Method -- 13. Single-Level Production Planning in Petrochemical Industries using Novel Computational Intelligence Algorithms -- 14. A Multi-Agent platform to support knowledge based modelling in engineering Design -- Part II. Applications: 15. Synthesis of reference trajectories for humanoid robot supported by genetic algorithm -- 16. Linked Simulation Optimization Model for Evaluation of Optimal Bank Protection Measures -- 17. A GA Based Iterative Model for Identification of Unknown Groundwater Pollution Sources Considering Noisy Data -- 18. Efficiency of Binary Coded Genetic Algorithm in Stability Analysis of an Earthen Slope -- 19. Corridor allocation as a constrained optimization problem using a permutation-based multi-objective genetic algorithm -- 20. The constrained single-row facility layout problem with repairing mechanisms -- 21. Geometric size optimization of annular step fin array for heat transfer by natural convection -- 22. Optimal control of saltwater intrusion in coastal aquifers using analytical approximation based on density dependent flow correction -- 23. Dynamic Nonlinear Active Noise Control. A Multi-Objective Evolutionary Computing Approach -- 24. Scheduling of Jobs on Dissimilar Parallel Machine using Computational Intelligence Algorithms -- 25. Branch-and-Bound Method for Just-in-Time Optimization of Radar Search Patterns -- 26. Optimization of the GIS based DRASTIC model for Groundwater Vulnerability Assessment.
520 3 _aThis book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.
988 _aPrimersemestre_2020_Engineering
650 7 _2embne
_aProceso en lenguaje natural (Informática)
_9158738
650 7 _2embne
_aBioinformática
_9160489
700 1 _aBennis, Fouad
_eeditor
700 1 _aBhattacharjya, Rajib Kumar
_eeditor
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783030264574
776 0 8 _iPrinted edition:
_z9783030264598
776 0 8 _iPrinted edition:
_z9783030264604
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-26458-1
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
_n0
998 _b04/2020
_dz
_eu
_zSI