High step-up interleaved dc/dc converter with high efficiency

Ye, Haixiong; Jin, Guangzhe; Fei, Wang; Ghadimi, Noradin

doi:10.1080/15567036.2020.1716111

Cited by 87 publications

(67 citation statements)

References 25 publications

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“…The application of image processing techniques for medical applications has increased rapidly in recent years. 2,3 Today, digital medical images are recorded and stored. However, interpreting the details of medical images is still time consuming.…”

Section: Introductionmentioning

confidence: 99%

An optimal brain tumor detection by convolutional neural network and Enhanced Sparrow Search Algorithm

Liu

Yuan

et al. 2021

Proc Inst Mech Eng H

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Precise and timely detection of brain tumor area has a very high effect on the selection of medical care, its success rate and following the disease process during treatment. Existing algorithms for brain tumor diagnosis have problems in terms of better performance on various brain images with different qualities, low sensitivity of the results to the parameters introduced in the algorithm and also reliable diagnosis of tumors in the early stages of formation. A computer aided system is proposed in this research for automatic brain tumors diagnosis. The method includes four main parts: pre-processing and segmentation techniques, features extraction and final categorization. Gray-level co-occurrence matrix (GLCM) and Discrete Wavelet Transform (DWT) were applied for characteristic extraction of the MR images which are then injected to an optimized convolutional neural network (CNN) for the final diagnosis. The CNN is optimized by a new design of Sparrow Search Algorithm classification (ESSA). Finally, a comparison of the results of the method with three state of the art technique on the Whole Brain Atlas (WBA) database to show its higher efficiency.

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Section: Introductionmentioning

confidence: 99%

An optimal brain tumor detection by convolutional neural network and Enhanced Sparrow Search Algorithm

Liu

Yuan

et al. 2021

Proc Inst Mech Eng H

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show abstract

“…The ANN is a widely used methodology in artificial intelligence, which is inspired by the human brain interactions between synapses and neurons. The ANN method is a good black box-based tool for classification of the nonlinear problems with the least attempts [ 10 , 11 , 12 , 13 , 14 , 15 , 16 ]. In recent years, a new kind of neural network has been proposed based on deep learning, which is known as convolutional neural network (CNN).…”

Section: Introductionmentioning

confidence: 99%

Computer-aided diagnosis of skin cancer based on soft computing techniques

et al. 2020

Self Cite

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Skin cancer is a type of disease in which malignant cells are formed in skin tissues. However, skin cancer is a dangerous disease, and an early detection of this disease helps the therapists to cure this disease. In the present research, an automatic computer-aided method is presented for the early diagnosis of skin cancer. After image noise reduction based on median filter in the first stage, a new image segmentation based on the convolutional neural network optimized by satin bowerbird optimization (SBO) has been adopted and its efficiency has been indicated by the confusion matrix. Then, feature extraction is performed to extract the useful information from the segmented image. An optimized feature selection based on the SBO algorithm is also applied to prune excessive information. Finally, a support vector machine classifier is used to categorize the processed image into the following two groups: cancerous and healthy cases. Simulations have been performed of the American Cancer Society database, and the results have been compared with ten different methods from the literature to investigate the performance of the system in terms of accuracy, sensitivity, negative predictive value, specificity, and positive predictive value.

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“…Another group of studies directly addresses the issue of demand‐side participation in the wholesale market by considering responsive loads as an independent market participant, which is priced to participate in demand response programs 17 . Some other studies consider the uses of traditional and also RE‐based resources to provide electrical and thermal loads in CHP systems, instantaneously.…”

Section: Introductionmentioning

confidence: 99%

A new configuration of autonomous CHP system based on improved version of marine predators algorithm: A case study

Wang

Wang²,

Zhang³

et al. 2021

Int Trans Electr Energ Syst

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Summary The present paper describes a new optimal design for an autonomous renewable energy‐based CHP system for a remote area in Zhidoi county, China. The configuration contains different parts of the electric heater (EH), photovoltaic‐thermal (PV/T), wind turbines (WTs), thermal energy storage (TES), and electrical energy storage (EES). The total annual cost (TAC) is utilized as a cost function of the system configuration and the idea is to minimize this function to access an optimal configuration. Due to the complicated nonlinear nature of this system, a metaheuristic‐based method, called Improved Marine Predators Algorithm (IMPA) has been introduced and designed. The reason for using this new algorithm is to cover the main drawbacks of most metaheuristics like better accuracy and higher convergence speed. To show the capability of the designed IMPA, it is validated by some different new metaheuristics from the literature. Afterward, the algorithm is used for system configuration optimization. Some sensitivity analysis is also investigated to shoe the method capability and the final results confirm the high ability of the proposed method for providing an optimal renewable energy‐based CHP system. The final results show a $56 307.74 value of TAC. The total efficiency of the system for the winter and the summers are 66% and 61%, respectively and the minimum total annual cost happens at AD = 0.8983. Finally, the minimum value of the total annual cost is achieved by the proposed method with 922.4 kWh.

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High step-up interleaved dc/dc converter with high efficiency

Cited by 87 publications

References 25 publications

An optimal brain tumor detection by convolutional neural network and Enhanced Sparrow Search Algorithm

An optimal brain tumor detection by convolutional neural network and Enhanced Sparrow Search Algorithm

Computer-aided diagnosis of skin cancer based on soft computing techniques

A new configuration of autonomous CHP system based on improved version of marine predators algorithm: A case study

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