Particle Swarm-Based Approach for Storage Efficiency Optimization of Supercapacitors

2019 ◽  
pp. 445-461
Author(s):  
Rudrendu Mahindar ◽  
Sahana Mukherjee ◽  
Sankhadeep Dutta ◽  
Tanusree Dutta ◽  
Rabindranath Ghosh
Keyword(s):  
Particle Swarm ◽  
Storage Efficiency ◽  
Efficiency Optimization

scholarly journals Storage Efficiency Optimization of a Supercapacitor Charged by a Photovoltaic Cell using Genetic Algorithm

IARJSET ◽  
2017 ◽  
Vol 4 (5) ◽  
pp. 217-224 ◽  
Author(s):  
Sachin Seth ◽  
Sudipto Mukherjee ◽  
Tanusree Dutta ◽  
Rabindranath Ghosh
Keyword(s):  
Genetic Algorithm ◽  
Photovoltaic Cell ◽  
Storage Efficiency ◽  
Efficiency Optimization

Energy storage efficiency optimization of methane reforming with CO2 reactors for solar thermochemical energy storage☆

2020 ◽  
Vol 266 ◽  
pp. 114788 ◽  
Author(s):  
Chen Chen ◽  
Mingmin Kong ◽  
Shuiqing Zhou ◽  
Abdon E. Sepulveda ◽  
Hui Hong
Keyword(s):  
Energy Storage ◽  
Methane Reforming ◽  
Storage Efficiency ◽  
Efficiency Optimization ◽  
Solar Thermochemical ◽  
Energy Storage Efficiency

Construction Energy Conservation Application Research Based on Swarm Intelligence Algorithm

2012 ◽  
Vol 442 ◽  
pp. 256-261 ◽  
Author(s):  
Yong Jun Zhang
Keyword(s):  
Energy Efficiency ◽  
Construction Materials ◽  
Particle Swarm ◽  
Building Energy ◽  
Particle Swarm Algorithm ◽  
Building Energy Efficiency ◽  
Efficiency Optimization ◽  
Intelligence Algorithm ◽  
Swarm Algorithm ◽  
Swarm Intelligence Algorithm

Genetic algorithm, particle swarm algorithm such as rise intelligence algorithm have unique advantages in multiple objective optimization areas, using the algorithm, based on architectural construction, materials, environment, climate, usage and features and other aspects of the overall optimization, can quickly and effectively realize the comprehensive effect of building energy efficiency optimization goal. This paper discusses the problem of multiple building energy efficiency, and for intelligent algorithm in building energy saving the optimization technology on the comprehensive introduction, finally how to particle swarm algorithm is applied to building energy efficiency optimization was attempted.

Smart teaching mode based on particle swarm image recognition and human-computer interaction deep learning

2020 ◽  
Vol 39 (4) ◽  
pp. 5699-5711
Author(s):  
Shirong Long ◽  
Xuekong Zhao
Keyword(s):  
Feature Extraction ◽  
Particle Swarm Optimization ◽  
Deep Learning ◽  
Real Time ◽  
Image Recognition ◽  
Particle Swarm ◽  
Learning Technology ◽  
Search Performance ◽  
Swarm Optimization ◽  
Teaching Mode

The smart teaching mode overcomes the shortcomings of traditional teaching online and offline, but there are certain deficiencies in the real-time feature extraction of teachers and students. In view of this, this study uses the particle swarm image recognition and deep learning technology to process the intelligent classroom video teaching image and extracts the classroom task features in real time and sends them to the teacher. In order to overcome the shortcomings of the premature convergence of the standard particle swarm optimization algorithm, an improved strategy for multiple particle swarm optimization algorithms is proposed. In order to improve the premature problem in the search performance algorithm of PSO algorithm, this paper combines the algorithm with the useful attributes of other algorithms to improve the particle diversity in the algorithm, enhance the global search ability of the particle, and achieve effective feature extraction. The research indicates that the method proposed in this paper has certain practical effects and can provide theoretical reference for subsequent related research.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

Adaptive Inertia Weight Particle Swarm Optimization For Linear and Nonlinear Channel Equalization

2012 ◽  
Vol 3 (4) ◽  
pp. 1-4
Author(s):  
Diana D.C Diana D.C ◽  
◽  
Joy Vasantha Rani.S.P Joy Vasantha Rani.S.P ◽  
Nithya.T.R Nithya.T.R ◽  
Srimukhee.B Srimukhee.B
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Channel Equalization ◽  
Swarm Optimization ◽  
Inertia Weight ◽  
Linear And Nonlinear
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