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A novel smart grid fault diagnosis algorithm based on optimized BP neural network

Peng Zhang, Na Liu, Bo-yang Qu, Jing Chang, Jun-ming Xiao, Qi-feng Zhao, Lin Man-man
2018 International Journal of Smart Grid and Clean Energy  
Considering that the structure of Smart Grid Fault Diagnosis Algorithm based on BP neural network became complex due to the increase of the sample dimension and the network fell easily into local maximums  ...  or minimums, genetic algorithm and rough set were combined to optimize the BP neural network.  ...  Conclusion A new Smart Grid Fault Diagnosis Algorithm of Optimizing BP Neural Network Based on Genetic Algorithm and Rough Set is proposed in this paper.  ... 
doi:10.12720/sgce.7.3.170-179 fatcat:b263yavxzvanzj2wekg5hc67si

Fault early warning of pitch system of wind turbine based on GA-BP neural network model

Sihan Chen, Yongguang Ma, Liangyu Ma, R. Weerasinghe, J. Wu, C.-H. Weng
2020 E3S Web of Conferences  
A fault early warning method based on genetic algorithm to optimize the BP neural network for the wind turbine pitch system is proposed.  ...  The BP neural network optimized by genetic algorithm is used to establish the model of the pitch system under normal working conditions.  ...  Using genetic algorithm to optimize BP neural network can solve its problems.  ... 
doi:10.1051/e3sconf/202019403005 fatcat:p5kes6up2bacxnvxfwgxnk6lgq

Machine Learning-Based Sensor Data Modeling Methods for Power Transformer PHM

Anyi Li, Xiaohui Yang, Huanyu Dong, Zihao Xie, Chunsheng Yang
2018 Sensors  
In particular, we apply the Cuckoo Search (CS) algorithm to optimize the Back-propagation (BP) neural network in order to build high performance fault diagnostics models.  ...  This paper proposed a machine learning-based methods for developing PHM models from sensor data to perform fault diagnostic for transformer systems in a smart grid.  ...  [24] proposed a deep learning method based on a convolutional neural network (CNN).  ... 
doi:10.3390/s18124430 fatcat:u6htevhufzbm3bzwr5u5xknp4a

Family History, Reproductive, and Lifestyle Risk Factors for Fibroadenoma and Breast Cancer

Jingmei Li, Keith Humphreys, Peh Joo Ho, Mikael Eriksson, Eva Darai-Ramqvist, Linda Sofie Lindström, Per Hall, Kamila Czene
2018 JNCI Cancer Spectrum  
Methods Using multistate survival analysis on a large dataset (n = 58 322), we examined the effects of BC risk factors on transitions between three states: event-free, biopsy-confirmed fibroadenoma, and  ...  More work is needed to understand the relationships between fibroadenoma and BC to identify women who are at high risk of developing BC after a fibroadenoma diagnosis.  ...  [24] proposed a deep learning method based on a convolutional neural network (CNN).  ... 
doi:10.1093/jncics/pky051 pmid:31360866 pmcid:PMC6650060 fatcat:4h2oh67vxzfsho7iwan5fbicki

Fault Diagnosis of Hydraulic Servo Valve Based on Genetic Optimization RBF-BP Neural Network

Li-Ping FAN, Chun-Yan LIU, Yi LIU
2014 Sensors & Transducers  
In this paper, RBF and BP neural network are integrated effectively to build a double hidden layers RBF-BP neural network for fault diagnosis.  ...  In the process of training the neural network, genetic algorithm (GA) is used to initialize and optimize the connection weights and thresholds of the network.  ...  Genetic optimization RBF-BP neural network is very useful for fault diagnosis on hydraulic servo valve.  ... 
doaj:9f1ae9783ddc416cbed574e02db7b669 fatcat:x52fdeoz55ca5lnapcjs673vg4

Fault Diagnosis of Automobile Engine Based on Improved BP Neutral Network

Yanjun Ling, Chuanming Niu, Xin Ning
2022 Wireless Communications and Mobile Computing  
algorithm (GA) optimization BP neural network fault diagnosis method.  ...  speed of the algorithm by introducing the momentum term, and the weights and thresholds of the neural network are optimized by using GA selection, crossover, and genetic characteristics, to propose a genetic  ...  genetic algorithm (GA) optimization BP neural network fault diagnosis method.  ... 
doi:10.1155/2022/2287776 fatcat:im7djutb7fh5nf4xilfqjsotzu

Computer Network Fault Diagnosis Based On Neural Network

Wang Qian
2015 International Journal of Future Generation Communication and Networking  
In this paper, the method is widely used, which is combined the self organizing feature map (SOM) neural network and multilayer feedforward neural network (BP): The result of the training samples using  ...  SOM neural network clustering algorithm is added to the original training samples and set a certain weight, through iterative update to the weight, in order to improve the convergence the speed of BP  ...  Shi Yongsheng and Song Yunxue overcomed the shortcoming of the single application of BP algorithm, using genetic algorithm (GA) to improve it, to establish a diag nosis model based on genetic algorithms  ... 
doi:10.14257/ijfgcn.2015.8.5.04 fatcat:k5bpkzupznbx3pexlz2fjmdhse

Artificial Intelligence and Its Applications 2014

Yudong Zhang, Saeed Balochian, Praveen Agarwal, Vishal Bhatnagar, Orwa Jaber Housheya
2016 Mathematical Problems in Engineering  
The genetic algorithm with modified genetic operators produced an average improvement of over 50%.  ...  The performance of the landslide prediction depends on the input factors beside the prediction method. In this research work, 14 input factors were used.  ...  The performance of the landslide prediction depends on the input factors beside the prediction method. In this research work, 14 input factors were used.  ... 
doi:10.1155/2016/3871575 fatcat:irj62qjsdzfu7h4fdslkgy5hny

Enhanced Distributed Parallel Firefly Algorithm Based on the Taguchi Method for Transformer Fault Diagnosis

Zhi-Jun Li, Wei-Gen Chen, Jie Shan, Zhi-Yong Yang, Ling-Yan Cao
2022 Energies  
To improve the reliability and accuracy of a transformer fault diagnosis model based on a backpropagation (BP) neural network, this study proposed an enhanced distributed parallel firefly algorithm based  ...  Finally, the proposed EDPFA was applied to a transformer fault diagnosis model by training the initial parameters of the BP neural network.  ...  The transformer fault diagnosis model based on a BP neural network. Figure 5 . 5 Figure 5. The transformer fault diagnosis model based on a BP neural network. Figure 6 . 6 Figure 6.  ... 
doi:10.3390/en15093017 fatcat:zljo5xd3kvd5pg5nrtmgzdbs5a

Fault diagnosis of oil pump based on high speed and precise genetic algorithm neural network

Meijuan Gao, Jingwen Tian, Liting Cao, Jin Xu
2008 2008 IEEE Conference on Cybernetics and Intelligent Systems  
According to the physical circumstances of oil pump, a fault diagnosis method of oil pump based on high speed and precise genetic algorithm neural network is presented in this paper.  ...  The high speed and precise genetic algorithm neural network is combined the adaptive and floating-point code genetic algorithm with BP which has higher accuracy and faster convergence speed.  ...  So in order to diagnose the faults of the oil pump effectively and in time in the petroleum production process, a fault diagnosis method based on the high speed and precise genetic algorithm neural network  ... 
doi:10.1109/iccis.2008.4670935 fatcat:lrjt3k5qojaibf757dlxinl6xe

A Fault Diagnosis Method for Oil Well Pump Using Radial Basis Function Neural Network Combined with Modified Genetic Algorithm

Deliang Yu, Yanmei Li, Hao Sun, Yulong Ren, Yongming Zhang, Weigui Qi
2017 Journal of Control Science and Engineering  
This paper presents a new method to diagnose oil well pump faults using a modified radial basis function neural network.  ...  The advantage of this new method is its use of a simple feature extraction method and advanced genetic algorithm to optimize the threshold and weight of the RBF neural network.  ...  To overcome these problems, 2 Journal of Control Science and Engineering this paper proposes a fault diagnosis method based on the multiple mutation adaptive genetic algorithm-radial basis function neural  ... 
doi:10.1155/2017/5710408 fatcat:tvywb3nssjfy3ligsm4yfxhoqi

Application of GLBP Algorithm in the Prediction of Building Energy Consumption

Dinghao Lv, Bocheng Zhong, Jing Luo
2015 International Journal of Advanced Computer Science and Applications  
Using BP neural network in past to predict the energy consumption of the building resulted in some shortcomings.  ...  First, genetic algorithm was used to optimize the weight and threshold of Artificial Neural Network (ANN). Levenberg-Marquardt algorithm was adopted to optimize the neural network training.  ...  Bingbing Shi [5] and others find that when using LM algorithm to improve the BP neural network, the BP network training speed is improved obviously, and the prediction error is smaller.  ... 
doi:10.14569/ijacsa.2015.060607 fatcat:oqxuk7kwcfb7tlkxtcu2boxztu

Review of Neural Network Algorithm and Its Application in Reactive Distillation

Huihui Wang, Ruyang Mo
2021 Asian Journal of Chemical Sciences  
Instead, neural network algorithms must be used.  ...  Artificial Neural Networks (ANN) can accurately identify and learn the potential relationship between input and output, and have self-learning capabilities and high fault tolerance, which can be used to  ...  In terms of classification, Sang et al. [38] uses genetic algorithm and BP neural network optimized support vector machine method to classify enterprises.  ... 
doi:10.9734/ajocs/2021/v9i319073 fatcat:xedwvxgxuvgs7cqj62ndqb7ln4

Special issue on machine learning for robotics

Wei Wei, Jinsong Wu, Chunsheng Zhu
2020 Journal of Ambient Intelligence and Humanized Computing  
The paper entitled "Robot Algorithm Based on Neural Network and Intelligent Predictive Control" provided by Yini Wang proposes a novel intelligent predictive control scheme that uses a neural network intelligent  ...  The paper entitled "Kinematics Model Identification and Motion Control of Robot Based on Fast Learning Neural Network" provided by Xuehong Sun introduces a new learning neural network structure, called  ...  The paper entitled "Inverse Kinematics Solution of Robotics Based on Neural Network Algorithms" provided by Ruihua Gao proposes a robotics inverse solution algorithm based on improved BP (back propagation  ... 
doi:10.1007/s12652-020-02567-x fatcat:bnebxk5sobfyvcnuv6amklm2e4

Neural network algorithm and its application in reactive distillation [article]

Huihui Wang, Ruyang Mo
2020 arXiv   pre-print
but must rely on neural network algorithms.  ...  Reactive distillation is a special distillation technology based on the coupling of chemical reaction and distillation.  ...  [35] uses genetic algorithm and BP neural network optimized support vector machine method to classify enterprises.  ... 
arXiv:2011.09969v1 fatcat:sc5w2pvdzfee3mtxyb3f7zpgfq
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