Coeval
发表于 2025-3-26 21:33:43
Bean Optimization Algorithm Based on Negative Binomial Distributionroposed many nature-inspired optimization algorithms. When solving some complex problems which cannot be solved by the traditional optimization algorithms easily, the nature-inspired optimization algorithms have their unique advantages. Inspired by the transmission mode of seeds, a novel evolutionar
hieroglyphic
发表于 2025-3-27 02:43:34
On the Application of Co-Operative Swarm Optimization in the Solution of Crystal Structures from X-Rthod does not need essential effort for its adjustment to the problem in hand but demonstrates high performance. This algorithm is compared with a sequential two-level genetic algorithm, a multi-population parallel genetic algorithm and a self-configuring genetic algorithm as well as with two proble
Paradox
发表于 2025-3-27 08:24:59
Swarm Diversity Analysis of Particle Swarm Optimizationnalyses the reasons leading to the loss of swarm diversity by computing and analyzing of the probabilistic characteristics of the learning factors in PSO. It also provides the relationship between the loss of swarm diversity and the probabilistic distribution and dependence of learning parameters. E
capsaicin
发表于 2025-3-27 10:19:36
A Self-learning Bare-Bones Particle Swarms Optimization Algorithm First, the expectation of Gaussian distribution in the updating equation is controlled by an adaptive factor, which makes particles emphasize on the exploration in earlier stage and the convergence in later stage. Second, SLBBPSO adopts a novel mutation to the personal best position (.) and the glo
广口瓶
发表于 2025-3-27 17:02:52
Improved DPSO Algorithm with Dynamically Changing Inertia Weightptimization algorithm and improve the optimization accuracy and stability of standard PSO algorithm. However, the accuracy of DPSO for solving the multi peak function will be obviously decreased. To solve the problem, we introduce the linearly decreasing inertia weight strategy and the adaptively ch
粘
发表于 2025-3-27 20:36:30
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FID
发表于 2025-3-27 23:32:05
A Fully-Connected Micro-extended Analog Computers Array Optimized by Particle Swarm Optimizermatical model and two uEAC extensions with minus-feedback and multiplication-feedback, respectively. Then a fully-connected uEACs array is proposed to enhance the computational capability, and to get an optimal uEACs array structure for specific problems, a comprehensive optimization strategy based
听写
发表于 2025-3-28 04:54:36
A Population-Based Clustering Technique Using Particle Swarm Optimization and K-Means. However, the performance of these hybrid clustering methods have not been extensively analyzed and compared with other competitive clustering algorithms. In the paper, five existing PSOs, which have shown promising performance for continuous function optimization, are hybridized separately with K-
moratorium
发表于 2025-3-28 08:49:51
A Novel Boundary Based Multiobjective Particle Swarm Optimizationhes the border of the objective space unlike other current proposals to look for the Pareto solution set to solve such problems. In addition, we apply the proposed method to other particle swarm optimization variants, which indicates the strategy is highly applicatory. The proposed approach is valid
prolate
发表于 2025-3-28 10:38:25
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