Intelligent Optimization Principles, Algorithms and Applications /
This textbook comprehensively explores the foundational principles, algorithms, and applications of intelligent optimization, making it an ideal resource for both undergraduate and postgraduate artificial intelligence courses. It remains equally valuable for active researchers and individuals engage...
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| Автори: | , , , |
|---|---|
| Співавтор: | |
| Формат: | Електронний ресурс eКнига |
| Мова: | Англійська |
| Опубліковано: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2024.
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| Редагування: | 1st ed. 2024. |
| Предмети: | |
| Онлайн доступ: | https://doi.org/10.1007/978-981-97-3286-9 |
| Теги: |
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| 245 | 1 | 0 | |a Intelligent Optimization |h [electronic resource] : |b Principles, Algorithms and Applications / |c by Changhe Li, Shoufei Han, Sanyou Zeng, Shengxiang Yang. |
| 250 | |a 1st ed. 2024. | ||
| 264 | 1 | |a Singapore : |b Springer Nature Singapore : |b Imprint: Springer, |c 2024. | |
| 300 | |a XXIII, 361 p. 152 illus., 63 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
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| 341 | 0 | |b Use of color is not sole means of conveying information |2 onix | |
| 341 | 0 | |b Use of high contrast between text and background color |2 onix | |
| 341 | 0 | |b Next / Previous structural navigation |2 onix | |
| 341 | 0 | |b All non-decorative content supports reading without sight |2 onix | |
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| 505 | 0 | |a chapter 1 Introduction -- chapter 2 Fundamentals -- chapter 3 Canonical Optimization Algorithms -- chapter 4 Basics of Evolutionary Computation Algorithms -- chapter 5 Popular Evolutionary Computation Algorithms -- chapter 6 Parameter Control and Policy Control -- chapter 7 Exploitation versus Exploration -- chapter 8 Multi-modal Optimization -- chapter 9 Multi-objective Optimization -- chapter 10 Constrained Optimization -- chapter 11 Dynamic Optimization.-chapter 12 Robust Optimization.-Chapter 13 Large-scale Global Optimization.-Chapter 14 Expensive Optimization -- Chapter 15 Real-world Applications. | |
| 520 | |a This textbook comprehensively explores the foundational principles, algorithms, and applications of intelligent optimization, making it an ideal resource for both undergraduate and postgraduate artificial intelligence courses. It remains equally valuable for active researchers and individuals engaged in self-study. Serving as a significant reference, it delves into advanced topics within the evolutionary computation field, including multi-objective optimization, dynamic optimization, constrained optimization, robust optimization, expensive optimization, and other pivotal scientific studies related to optimization. Designed to be approachable and inclusive, this textbook equips readers with the essential mathematical background necessary for understanding intelligent optimization. It employs an accessible writing style, complemented by extensive pseudo-code and diagrams that vividly illustrate the mechanisms, principles, and algorithms of optimization. With a focus on practicality, this textbook provides diverse real-world application examples spanning engineering, games, logistics, and other domains, enabling readers to confidently apply intelligent techniques to actual optimization problems. Recognizing the importance of hands-on experience, the textbook introduces the Open-source Framework for Evolutionary Computation platform (OFEC) as a user-friendly tool. This platform serves as a comprehensive toolkit for implementing, evaluating, visualizing, and benchmarking various optimization algorithms. The book guides readers on maximizing the utility of OFEC for conducting experiments and analyses in the field of evolutionary computation, facilitating a deeper understanding of intelligent optimization through practical application. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Algorithms. | |
| 650 | 0 | |a Mathematical optimization. | |
| 650 | 0 | |a Computational intelligence. | |
| 650 | 1 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Design and Analysis of Algorithms. |
| 650 | 2 | 4 | |a Continuous Optimization. |
| 650 | 2 | 4 | |a Computational Intelligence. |
| 700 | 1 | |a Han, Shoufei. |e author. |0 (orcid)0000-0003-3583-7735 |1 https://orcid.org/0000-0003-3583-7735 |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 700 | 1 | |a Zeng, Sanyou. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 700 | 1 | |a Yang, Shengxiang. |e author. |0 (orcid)0000-0001-7222-4917 |1 https://orcid.org/0000-0001-7222-4917 |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
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| 776 | 0 | 8 | |i Printed edition: |z 9789819732852 |
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| 856 | 4 | 0 | |u https://doi.org/10.1007/978-981-97-3286-9 |
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