Intelligent MPPT for photovoltaic panels using a novel fuzzy logic and artificial neural networks based on evolutionary algorithms

Fathi, Milad; Parian, Jafar Amiri

doi:10.1016/j.egyr.2021.02.051

Cited by 103 publications

(30 citation statements)

References 42 publications

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“…Pooling uses a feature value to replace a region in the original feature map, which can semantically merge similar features, so the feature vector can be significantly reduced. Pooling functions include methods such as maximum pooling, average pooling, and random pooling [ 16 ].…”

Section: Methods Of Machine Vision and Intelligent Algorithms Based O...mentioning

confidence: 99%

Machine Vision and Intelligent Algorithm Based on Neural Network

Sun

2022

Computational Intelligence and Neuroscience

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Neural network algorithms and intelligent algorithms are hot topics in the field of deep learning. In this study, the neural network algorithm and intelligence are optimized, and it is used in simulation experiments to improve the target image recognition ability of the algorithm in the machine vision environment. First, this paper introduces the application of neural networks in the field of machine vision. Second, in the experiment, the improved VGG-16 convolutional neural network (CNN) model is applied to metal block defect detection. Experimental results show that the optimized network can classify metal block defects with the maximum accuracy of 99.28%. Then, the intelligent algorithm based on neural network is studied, and the CIFAR-10 data set is taken as the experimental target for training test and verification test. Using BP algorithm, particle swarm optimization algorithm (PSO-BP), and improved neural network algorithm, respectively, the convergence speed of ICS algorithm based on BP neural network is compared. In contrast, ICS-BP algorithm has the fastest convergence speed and converges when the number of iterations is 32, followed by PSO-BP algorithm.

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Section: Methods Of Machine Vision and Intelligent Algorithms Based O...mentioning

confidence: 99%

Machine Vision and Intelligent Algorithm Based on Neural Network

Sun

2022

Computational Intelligence and Neuroscience

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“…The traditional way of e-mail submission will be used in the use of journal departments and conferences. But the defect of e-mail contribution is also very obvious and more and more prominent [ 28 , 29 ]. Journal workers need to register, mark, typeset, and check the manuscripts.…”

Section: Research On the Establishment Technology Of Manuscript Management System Based On Fgnn And Modelingmentioning

confidence: 99%

[Retracted] Optimization and Simulation of Manuscript Management System Based on Fuzzy Genetic Neural Network

Sun

2021

Computational Intelligence and Neuroscience

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Manuscript management plays an important role in the whole periodical industry. Journals and magazine society receive different types of contribution documents from all over the world. Many submission files are mostly transmitted by e-mail, but there are some hidden disadvantages in e-mail. In view of this situation, this paper studies the establishment and optimization simulation of manuscript management system based on fuzzy genetic neural network (FGNN). On the basis of genetic neural network, combined with the advantages of FNN neural network algorithm, a FGNN structure is established to optimize the system, which is helpful to the learning and expression ability of the whole system. The results show that the FGNN can extract and express the structured data, and the submission management system runs faster. Then, UML modeling and PHP framework are used to realize the design and establishment of the system, and the simulation model of contribution system is constructed. The innovation of this study is to combine genetic neural network with FNN neural network, which can query, manage, and classify manuscripts quickly. It also improves the complex submission system and optimizes the submission process. The whole journal editing work has been effectively improved.

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“…However, the LM algorithm performs better in the correlation between input-output, dataset training, and error. A fuzzy logic, particle swarm optimization (PSO), and imperialist competitive algorithm are proposed in [28], where it is declared that the fuzzy logic is less complicated, faster, more accurate, and more stability then the other three algorithms. The authors have explored a hybrid shuffled frog leaping and pattern search (HSFL-PS) algorithm in [29] for optimizing ANNbased MPPT in a grid-tied PV system.…”

Section: Related Workmentioning

confidence: 99%

Solar Power System Assessments Using ANN and Hybrid Boost Converter Based MPPT Algorithm

et al. 2021

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The load pressure on electrical power system is increased during last decade. The installation of new power generators (PGs) take huge time and cost. Therefore, to manage current power demands, the solar plants are considered a fruitful solution. However, critical caring and balance output power in solar plants are the highlighted issues. Which needs a proper procedure in order to minimize balance output power and caring issues in solar plants. This paper investigates artificial neural network (ANN) and hybrid boost converter (HBC) based MPPT for improving the output power of solar plants. The proposed model is analyzed in two steps, the offline step and the online step. Where the offline status is used for training various terms of ANNs in terms of structure and algorithm while in the online step, the online procedure is applied with optimum ANN for maximum power point tracking (MPPT) using traditional converter and hybrid converter in solar plants. Moreover, a detail analytical framework is studied for both proposed steps. The mathematical and simulation approaches show that the presented model efficiently regulate the output of solar plants. This technique is applicable for current installed solar plants which reduces the cost per generation.

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Intelligent MPPT for photovoltaic panels using a novel fuzzy logic and artificial neural networks based on evolutionary algorithms

Cited by 103 publications

References 42 publications

Machine Vision and Intelligent Algorithm Based on Neural Network

Machine Vision and Intelligent Algorithm Based on Neural Network

[Retracted] Optimization and Simulation of Manuscript Management System Based on Fuzzy Genetic Neural Network

Solar Power System Assessments Using ANN and Hybrid Boost Converter Based MPPT Algorithm

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