With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distributi...With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.展开更多
In recent years,the problem of privacy leakage has attracted increasing attentions.Therefore,machine learning privacy protection becomes crucial research topic.In this paper,the Paillier homomorphic encryption algorit...In recent years,the problem of privacy leakage has attracted increasing attentions.Therefore,machine learning privacy protection becomes crucial research topic.In this paper,the Paillier homomorphic encryption algorithm is proposed to protect the privacy data.The original LeNet-5 convolutional neural network model was first improved.Then the activation function was modified and the C5 layer was removed to reduce the number of model parameters and improve the operation efficiency.Finally,by mapping the operation of each layer in the convolutional neural network from the plaintext domain to the ciphertext domain,an improved LeNet-5 model that can run on encrypted data was constructed.The purpose of using machine learning algorithmwas realized and privacywas ensured at the same time.The analysis shows that the model is feasible and the efficiency is improved.展开更多
基金supported by the State Grid Corporation of China(KJ21-1-56).
文摘With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.
基金The National Natural Science Foundation of China(No.61572521)Engineering University of PAP Innovation Team Science Foundation(No.KYTD201805)Natural Science Basic Research Plan in Shaanxi Province of China(2021JM252).
文摘In recent years,the problem of privacy leakage has attracted increasing attentions.Therefore,machine learning privacy protection becomes crucial research topic.In this paper,the Paillier homomorphic encryption algorithm is proposed to protect the privacy data.The original LeNet-5 convolutional neural network model was first improved.Then the activation function was modified and the C5 layer was removed to reduce the number of model parameters and improve the operation efficiency.Finally,by mapping the operation of each layer in the convolutional neural network from the plaintext domain to the ciphertext domain,an improved LeNet-5 model that can run on encrypted data was constructed.The purpose of using machine learning algorithmwas realized and privacywas ensured at the same time.The analysis shows that the model is feasible and the efficiency is improved.
