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Download e-book for iPad: Advances in Swarm Intelligence: 5th International by Ying Tan, Yuhui Shi, Carlos Coello Coello

By Ying Tan, Yuhui Shi, Carlos Coello Coello

ISBN-10: 3319118560

ISBN-13: 9783319118567

ISBN-10: 3319118579

ISBN-13: 9783319118574

This publication and its spouse quantity, LNCS vol. 8794 and 8795 represent the court cases of the fifth foreign convention on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised complete papers offered have been conscientiously reviewed and chosen from 198 submissions. The papers are prepared in 18 cohesive sections, three precise classes and one aggressive consultation protecting all significant themes of swarm intelligence examine and improvement comparable to novel swarm-based seek equipment; novel optimization set of rules; particle swarm optimization; ant colony optimization for traveling salesman challenge; synthetic bee colony algorithms; synthetic immune process; evolutionary algorithms; neural networks and fuzzy equipment; hybrid equipment; multi-objective optimization; multi-agent structures; evolutionary clustering algorithms; class equipment; GPU-based equipment; scheduling and course making plans; instant sensor networks; energy method optimization; swarm intelligence in photo and video processing; functions of swarm intelligence to administration difficulties; swarm intelligence for real-world application.

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Additional info for Advances in Swarm Intelligence: 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I

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Li The zero-one matrix A = {aij }m×n represents the problem instance, and aij = 1 means subset Sj is able to cover the element i. For each variable xj = 1 indicates that Sj is selected, and 0 otherwise. In literature, the SCP is also viewed as to find a set of columns to cover all the rows at the minimal total cost, where N is the set of all columns that each has a cost, M is the set of rows that need to be covered. The SCP is NP-hard in the strong sense [10], thus no complete algorithms with polynomial time complexity are known for SCP.

We repeated the same previous experiment, but this time we measured the flow of pedestrian traffic rather than the average velocity. 5 shows the comparison of the flow rates between PHuNAC model and real data. We observe that the flow rate curve of our model is very close to the flow rates curve representing real data. 16 O. Beltaief, S. El Hadouaj, and K. Ghedira Fig. 4. Comparison of average velocity curves Fig. 5. Comparison of flow rates curves 5 Conclusion We present in this work the PHuNAC model which is based on multi-agent systems and that includes the major psychological factors.

BLA, which originated from benchmarking theory of business management, is different from the EIOMs, which stem from the biological activities of nature. So BLA is brand new and it is a newborn member of the family comprising the modern intelligent optimization methods. However, as other optimization methods, BLA also involved a number of controls parameters, such as learning rates, etc. and how to set these controls parameters to optimize BLA to achieve the best effect, which itself is also a combinatorial optimization problem, is one of our next research topics.

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Advances in Swarm Intelligence: 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I by Ying Tan, Yuhui Shi, Carlos Coello Coello

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