Research on Speed Optimization Strategy of Hybrid Electric Vehicle Queue Based on Particle Swarm Optimization

Wang, Shaohua; Yu, Chengquan; Shi, Dehua; Sun, Xiaoyun

doi:10.1155/2018/6483145

“…In the particle swarm iteration, the speed and position of the k + 1-th iteration are updated as follows [14]:…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

Particle swarm optimization in image processing of power flow learning distribution

Huang

¹

2021

Discov Internet Things

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In order to realize the coordination and integration optimization of the power system itself, this paper constructed the mathematical model of the hybrid power system and solved the multi-objective optimization problem of the heating system through the optimized particle swarm optimization algorithm. Based on the back-to-back VSC-HVDC grid-connected composite system, this paper studied the integrated control strategy of the device to achieve the simultaneous parallel and tie line currents. At the same time, this paper simplified and improved the proposed disassembly criteria for grid-connected composite devices and integrated them into the grid-connected composite device. In addition, on this basis, the integrated control of the three functions of de-listing, juxtaposition and tie line power adjustment of the same device was further studied. Simulation studies show that the proposed algorithm has certain effects and can provide theoretical reference for subsequent related research.

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“…In the particle swarm iteration, the speed and position of the 1 k  -th iteration are updated as follows [14] :…”

Section: Figure 1 Schematic Diagram Of the Particle Search Processmentioning

confidence: 99%

Particle Swarm Optimization in Image Processing of Power Flow Learning Distribution

Huang

¹

2020

Preprint

0

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In order to realize the coordination and integration optimization of the power system itself, this paper constructed the mathematical model of the hybrid power system and solved the multi-objective optimization problem of the heating system through the optimized particle swarm optimization algorithm. Based on the back-to-back VSC-HVDC grid-connected composite system, this paper studied the integrated control strategy of the device to achieve the simultaneous parallel and tie line currents. At the same time, this paper simplified and improved the proposed disassembly criteria for grid-connected composite devices and integrated them into the grid-connected composite device. In addition, on this basis, the integrated control of the three functions of de-listing, juxtaposition and tie line power adjustment of the same device was further studied. Simulation studies show that the proposed algorithm has certain effects and can provide theoretical reference for subsequent related research.

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“…Some of the vast used algorithms are genetic algorithm, 16,17 ant colony optimization, 18 particle swarm optimization, 19–21 artificial bee colony (ABC), 22 and cuckoo search (CS) algorithm 23 . These models are used for solving numerical optimization problems and shown its significance towards global optimal solutions 24–26 . CS is one among these algorithms that starts from exploration initially and ends with exploitation capability in the given search space.…”

Section: Introductionmentioning

confidence: 99%

“…23 These models are used for solving numerical optimization problems and shown its significance towards global optimal solutions. [24][25][26] CS is one among these algorithms that starts from exploration initially and ends with exploitation capability in the given search space. This seems to be finding better optimized result when compared with other existing algorithms.…”

Section: Introductionmentioning

confidence: 99%

Enriched cluster head selection using augmented bifold cuckoo search algorithm for edge‐based internet of medical things

Anguraj

¹

,

Thirugnanasambandam²,

R.S

³

et al. 2021

Int J Communication

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Summary Healthcare organizations are appending advanced scientific tools for processing digital data effectively due to enterprise demands. Among the recent tools, edge computing plays a vital role in aggregation and dissemination of data from the healthcare monitoring devices. A vital challenge in edge computing‐based Internet of Medical Things (IoMT) systems are energy‐efficient monitoring devices which in turn improves the overall lifetime of the network thus in turn improves the quality of monitoring system. In recent years, a significant number of approaches are developed for solving energy efficient communication protocols for IoMT. Clustering is one effective method to reduce the overall energy consumption by the medical wireless devices. The major drawback of the existing models is the sustainability of the network. In this paper, an evolutionary‐based cluster head selection technique is proposed, namely, augmented bifold cuckoo search algorithm (ABCSA). A novel binary model is also developed for handling the binary solution space. The experimental analysis of the proposed model has been evaluated and compared with the existing model to prove it significance. And as a result on comparing with the existing models, proposed ABCSA outperforms the existing models significantly.

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Research on Speed Optimization Strategy of Hybrid Electric Vehicle Queue Based on Particle Swarm Optimization

Cited by 15 publications

References 27 publications

Particle swarm optimization in image processing of power flow learning distribution

Particle swarm optimization in image processing of power flow learning distribution

Particle Swarm Optimization in Image Processing of Power Flow Learning Distribution

Enriched cluster head selection using augmented bifold cuckoo search algorithm for edge‐based internet of medical things

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