Evolutionary and swarm intelligence algorithms / edited by Jagdish Chand Bansal, Pramod Kumar Singh, Nikhil R. Pal.
نوع المادة :
نصاللغة: الإنجليزية السلاسل:Studies in Computational Intelligence ; 779الناشر:Cham : Springer International Publishing : Imprint: Springer, 2019الطبعات:1st ed. 2019وصف:x, 190 pages : illustrations ; 24 cmنوع المحتوى:- text
- unmediated
- volume
- 9783030082291
- Q337.3 .E965 2019
| نوع المادة | المكتبة الحالية | رقم الطلب | رقم النسخة | حالة | تاريخ الإستحقاق | الباركود | |
|---|---|---|---|---|---|---|---|
كتاب
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UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | Q337.3 .E965 2019 (إستعراض الرف(يفتح أدناه)) | C.1 | Library Use Only | داخل المكتبة فقط | 30020000207200 |
Browsing UAE Federation Library | مكتبة اتحاد الإمارات shelves, Shelving location: General Collection | المجموعات العامة إغلاق مستعرض الرف(يخفي مستعرض الرف)
| Q336 P37 1998 Artificial Intelligence and software engineering : understanding the promise of the future / | Q337.3 .A487 2018 Swarms and network intelligence in search / | Q337.3 .A487 2018 Swarms and network intelligence in search / | Q337.3 .E965 2019 Evolutionary and swarm intelligence algorithms / | Q337.3 .I56 2012 Innovations and developments of swarm intelligence applications / | Q337.3 .I56 2012 Innovations and developments of swarm intelligence applications / | Q337.3 .R43 2013 Recent algorithms and applications in swarm intelligence research / |
Swarm and Evolutionary Computation -- Particle Swarm Optimization -- Artificial Bee Colony Algorithm Variants and Its Application to Colormap Quantization -- Spider Monkey Optimization Algorithm -- Genetic Algorithm and Its Advances in Embracing Memetics -- Constrained Multi-Objective Evolutionary Algorithm -- Genetic Programming for Classification and Feature Selection -- Genetic Programming for Job Shop Scheduling -- Evolutionary Fuzzy Systems: A Case Study for Intrusion Detection Systems.
This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.
