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200224 ||| eng |
| 020 |
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|a 9783030264581
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| 100 |
1 |
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|a Bennis, Fouad
|e [editor]
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| 245 |
0 |
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|a Nature-Inspired Methods for Metaheuristics Optimization
|h Elektronische Ressource
|b Algorithms and Applications in Science and Engineering
|c edited by Fouad Bennis, Rajib Kumar Bhattacharjya
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| 250 |
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|a 1st ed. 2020
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2020, 2020
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| 300 |
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|a XIII, 502 p. 252 illus., 110 illus. in color
|b online resource
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| 505 |
0 |
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|a 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 --
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| 505 |
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|a Part 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 --
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| 505 |
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|a 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
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| 653 |
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|a Mechanics, Applied
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| 653 |
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|a Heat engineering
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| 653 |
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|a Operations Research, Management Science
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| 653 |
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|a Operations research
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| 653 |
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|a Industrial engineering
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| 653 |
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|a Management science
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| 653 |
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|a Thermodynamics
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| 653 |
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|a Water
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| 653 |
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|a Computational intelligence
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| 653 |
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|a Heat transfer
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| 653 |
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|a Computational Intelligence
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| 653 |
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|a Engineering Mechanics
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| 653 |
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|a Industrial and Production Engineering
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| 653 |
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|a Mass transfer
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| 653 |
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|a Engineering Thermodynamics, Heat and Mass Transfer
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| 653 |
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|a Hydrology
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| 653 |
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|a Production engineering
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| 700 |
1 |
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|a Bhattacharjya, Rajib Kumar
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Modeling and Optimization in Science and Technologies
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| 028 |
5 |
0 |
|a 10.1007/978-3-030-26458-1
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-030-26458-1?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 003
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| 520 |
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|a This 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
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