Hybrid intelligent water drop bundled wavelet neural network to solve the islanding detection by inverter-based DG

Hagh, Mehrdad Tarafdar; Ebrahimian, Homayoun; Ghadimi, Noradin

doi:10.1007/s11708-014-0337-3

Cited by 71 publications

(11 citation statements)

References 27 publications

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“…The most significant advantage of this learning method is feature learning, which is an approach for the automatic extraction of features from low‐level inputs. In this study, a deep neural network was used for diagnosis 18 . A deep neural network is a network with several hidden layers within it to solve the problems considered 19 .…”

Section: Convolutional Neural Networkmentioning

confidence: 99%

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RETRACTED: Novel computer‐aided lung cancer detection based on convolutional neural network‐based and feature‐based classifiers using metaheuristics

Guo

et al. 2021

Int J Imaging Syst Tech

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This study proposes a lung cancer diagnosis system based on computed tomography (CT) scan images for the detection of the disease. The proposed method uses a sequential approach to achieve this goal. Consequently, two well‐organized classifiers, the convolutional neural network (CNN) and feature‐based methodology, have been used. In the first step, the CNN classifier is optimized using a newly designed optimization method called the improved Harris hawk optimizer. This method is applied to the dataset, and the classification is commenced. If the disease cannot be detected via this method, the results are conveyed to the second classifier, that is, the feature‐based method. This classifier, including Haralick and LBP features, is subsequently applied to the received dataset from the CNN classifier. Finally, if the feature‐based method also does not detect cancer, the case study is healthy; otherwise, the case study is cancerous.

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Section: Convolutional Neural Networkmentioning

confidence: 99%

“…In this study, a deep neural network was used for diagnosis. 18 A deep neural network is a network with several hidden layers within it to solve the problems considered. 19 CNNs are one of the most well-known deep neural networks.…”

Section: Convolutional Neural Networkmentioning

confidence: 99%

RETRACTED: Novel computer‐aided lung cancer detection based on convolutional neural network‐based and feature‐based classifiers using metaheuristics

Guo

et al. 2021

Int J Imaging Syst Tech

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“…Wavelet transformations are among the tools that have many applications in various branches of science and engineering, particularly artificial intelligence, machine learning, time series prediction, and pattern recognition. 28 The wavelet theory is a generalization of the Fourier transforms theory and series. It compensates for the weaknesses of Fourier analysis in local performance and modeling of short-term behaviors.…”

Section: Discrete Wavelet Transformmentioning

confidence: 99%

RETRACTED: Optimal brain tumor diagnosis based on deep learning and balanced sparrow search algorithm

Liu

Yuan

et al. 2021

Int J Imaging Syst Tech

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“…Only through the solar panel can we convert the solar energy that we can't use into the power we need. The material of solar panels is semiconductor, mainly crystalline silicon [17][18][19][20]. These crystalline silicon have photosensitive properties.…”

Section: Structure and Working Principle Of Photovoltaic Cellsmentioning

confidence: 99%

Solar Maximum Power Point Tracking Algorithm Based on Wavelet Neural Network

2023

J. Appl. Data Sci.

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With the development of human civilization, the shortage of resources and environmental pollution are increasing. Renewable energy is the only way to solve the problem of harmonious coexistence between human civilization and the environment. More and more of them have come into our lives to reduce the burden of the earth and benefit mankind. Nowadays, due to the increasing gap of traditional power supply, solar energy has become a mainstream renewable energy, with more and more applications, to provide us with green energy and improve our lives. The research on the application of solar energy systems is of great academic value. This paper mainly studies the solar maximum power point tracking (MPPT) algorithm based on wavelet neural network (WNN). This paper analyzes several common maximum power tracking control methods, describes the structure design of WNN maximum power tracking control algorithm, and describes the structure and working principle of photovoltaic cells. In this paper, the output power of MPPT mode is analyzed and compared by simulating the use of solar photovoltaic systems. In the meantime, the output voltage of the solar charging panel in the charging process is studied. The experimental results show that the output power of the power supply in MPPT mode is kept at 0.2, and the output power of the solar panel is improved at every moment with the change of the external environment. At 9 o'clock, the output voltage of the solar panel is 3.6, and at 11 o'clock, the output voltage is 4.11.

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Hybrid intelligent water drop bundled wavelet neural network to solve the islanding detection by inverter-based DG

Cited by 71 publications

References 27 publications

RETRACTED: Novel computer‐aided lung cancer detection based on convolutional neural network‐based and feature‐based classifiers using metaheuristics

RETRACTED: Novel computer‐aided lung cancer detection based on convolutional neural network‐based and feature‐based classifiers using metaheuristics

RETRACTED: Optimal brain tumor diagnosis based on deep learning and balanced sparrow search algorithm

Solar Maximum Power Point Tracking Algorithm Based on Wavelet Neural Network

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