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《Journal of Lanzhou University of Arts and Science(Natural Science Edition)》 2019-03
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Design and Optimization of Neural Network Security Based on Intelligent Optimization Algorithm

LI Ming-dong;LI Xue-zhu;WANG Ying;XU Xiao-xue;School of Information Engineering, Suzhou University;  
In order to solve problems of inaccurate network security prediction caused by slow convergence speed, imperfect evaluation index and imperfect model parameters, a neural network state evaluation and prediction optimization model based on intelligent optimization algorithm is designed. Firstly, based on the parallelism and efficiency of intelligent optimization algorithm, the evaluation of neural network is optimized, and the corresponding security level is divided. Secondly, the ant colony algorithm is used to obtain the source code value of the neural network state prediction model and optimize it to make the neural network state more efficient and stable. Experiment is designed for each model to verify the optimization and improvement of the neural network model by genetic algorithm.
【Fund】: 2018年安徽省自然科学研究重点项目“多维社交网络结构影响下的信息传播研究”(KJ2018A0448);; 宿州学院2018年质量工程重点教学研究项目“3Acloud思维导图在面向对象程序设计教学中的创新模式研究”(szxy2018jyxm01);; 2018年教育部产学合作协同育人项目“新工科教育理念下的工程师计划班”(201802203001)
【CateGory Index】: TP393.08;TP18
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