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Titlebook: Advances in Swarm Intelligence; 8th International Co Ying Tan,Hideyuki Takagi,Yuhui Shi Conference proceedings 2017 Springer International

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樓主: Ingrown-Toenail
41#
發(fā)表于 2025-3-28 15:13:04 | 只看該作者
42#
發(fā)表于 2025-3-28 21:45:05 | 只看該作者
Capturing Trust in Social Web Applicationshe paper, we, therefore, first model human behaviors and then build a simulation model including the model. The model of human behaviors focuses on physical movement and free will to decide a time of interactions with others. Furthermore, we attempt to understand the EC though simulations using the built simulation model.
43#
發(fā)表于 2025-3-28 23:16:58 | 只看該作者
https://doi.org/10.1007/978-1-84800-356-9chmark functions and three performance criteria, varying the algorithm parameters. The most promising setup is compared with a deterministic particle swarm optimization and a DIviding RECTangles algorithm, and applied to two hull-form optimization problems, showing a very promising performance.
44#
發(fā)表于 2025-3-29 05:27:13 | 只看該作者
A Non-reductionist Approach to Trustwasting computational efforts incurred in the previous generations. Numerical experiments on 10 well-known benchmark functions are conducted to evaluate the performance of the TLFBO, and experimental results show that the proposed TLFBO has a superior and competitive capability in solving continuous optimisation problems.
45#
發(fā)表于 2025-3-29 08:55:20 | 只看該作者
Trajectory Indexing and Retrievald to mutate the equally divided population. Accordingly, five variants of MBOs are proposed with new initialization strategy. By comparing five variants of MBOs with the basic MBO algorithm, the experimental results presented clearly demonstrate five variants of MBOs have much better performance than the basic MBO algorithm.
46#
發(fā)表于 2025-3-29 13:24:00 | 只看該作者
https://doi.org/10.1007/978-3-642-27473-2g of local search. The test results on eight multimodal benchmark functions demonstrate the performance superiority of ALS-HCLPSO. And comparison results on six advanced PSO variants further test the validity and superiority of ALS-HCLPSO algorithm.
47#
發(fā)表于 2025-3-29 15:48:16 | 只看該作者
48#
發(fā)表于 2025-3-29 20:26:51 | 只看該作者
Building a Simulation Model for Distributed Human-Based Evolutionary Computationhe paper, we, therefore, first model human behaviors and then build a simulation model including the model. The model of human behaviors focuses on physical movement and free will to decide a time of interactions with others. Furthermore, we attempt to understand the EC though simulations using the built simulation model.
49#
發(fā)表于 2025-3-30 03:29:12 | 只看該作者
Dolphin Pod Optimizationchmark functions and three performance criteria, varying the algorithm parameters. The most promising setup is compared with a deterministic particle swarm optimization and a DIviding RECTangles algorithm, and applied to two hull-form optimization problems, showing a very promising performance.
50#
發(fā)表于 2025-3-30 04:18:39 | 只看該作者
Teaching-Learning-Feedback-Based Optimizationwasting computational efforts incurred in the previous generations. Numerical experiments on 10 well-known benchmark functions are conducted to evaluate the performance of the TLFBO, and experimental results show that the proposed TLFBO has a superior and competitive capability in solving continuous optimisation problems.
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