A new method for the informed discovery of resources in the grid system using particle swarm optimization algorithm (RDT_PSO)

Abdeyazdan, Marjan

doi:10.1007/s11227-017-2090-y

Cited by 4 publications

(2 citation statements)

References 29 publications

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“…e courseware development process shown in the table above is an indispensable link in actual work, but each link has a different depth, and its courseware will have different effects. Due to the limitation of energy and time in practice, it can be considered according to the specific situation, which link to focus on [28].…”

Section: Multimedia Computermentioning

confidence: 99%

Multimedia Computer-Aided Teaching Platform Based on Particle Swarm Optimization Algorithm

Jiang

2022

Security and Communication Networks

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This paper mainly expounds the research hotspots and trends of computer-aided teaching platforms in view of particle swarm optimization algorithm and introduces current situation of computer-aided teaching platforms. This paper analyzes the realization of the core business system of the computer help education platform. And it puts forward the optimization idea of multimedia compute help education platform in view of particle swarm optimization algorithm. The experimental results illustrate Za = 1.42 when students in two classes use the computer-aided teaching platform before optimization. It shows that, at the 0.05 obvious level, there is no important objection in the scores of the two groups of students in the test. When the students in the experimental class used the optimized computer-aided teaching platform, Zb = 3.67, indicating that, at the 0.01 significant level, the performance of the students in the control class was significantly lower than that of the students in the experimental class.

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Section: Multimedia Computermentioning

confidence: 99%

Multimedia Computer-Aided Teaching Platform Based on Particle Swarm Optimization Algorithm

Jiang

2022

Security and Communication Networks

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“…By hybridizing PSO with GA for performance enhancement, Gong et al (2017) proposed genetic learning particle swarm optimization (GL-PSO). Abdeyazdan (2017) introduced a new method for the informed discovery of resources in the grid system using the PSO algorithm. Bonyadi and Michalewicz (2017) investigated the movement patterns of a particle in the PSO algorithm.…”

Section: Introductionmentioning

confidence: 99%

A novel PGSA–PSO hybrid algorithm for structural optimization

Jiang

Lin

Shi

et al. 2019

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Purpose The purpose of this paper is to propose a new hybrid algorithm, named improved plant growth simulation algorithm and particle swarm optimization hybrid algorithm (PGSA–PSO hybrid algorithm), for solving structural optimization problems. Design/methodology/approach To further enhance the optimization efficiency and precision of this algorithm, the optimization solution process of PGSA–PSO comprises two steps. First, an excellent initial growth point is selected by PSO. Then, the global optimal solution can be obtained quickly by PGSA and its improved strategy called growth space adjustment strategy. A typical mathematical example is provided to verify the capacity of the new hybrid algorithm to effectively improve the global search capability and search efficiency of PGSA. Moreover, PGSA–PSO is applied to the optimization design of a suspended dome structure. Findings Through typical mathematical example, the improved strategy can improve the optimization efficiency of PGSA considerably, and an initial growth point that falls near the global optimal solution can be obtained. Through the optimization of the pre-stress of a suspended dome structure, compared with other methods, the hybrid algorithm is effective and feasible in structural optimization. Originality/value Through the examples of suspended dome structure, it shows that the optimization efficiency and precision of PGSA–PSO are better than those of other algorithms and methods. PGSA–PSO is effective and feasible in structural optimization problems such as pre-stress optimization, size optimization, shape optimization and even topology optimization.

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