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Network Intrusion Traffic Detection Based on Feature Extraction 被引量:1
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作者 Xuecheng Yu Yan Huang +2 位作者 Yu Zhang Mingyang Song Zhenhong Jia 《Computers, Materials & Continua》 SCIE EI 2024年第1期473-492,共20页
With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(... With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(IDS).However,both unsupervised and semisupervised anomalous traffic detection methods suffer from the drawback of ignoring potential correlations between features,resulting in an analysis that is not an optimal set.Therefore,in order to extract more representative traffic features as well as to improve the accuracy of traffic identification,this paper proposes a feature dimensionality reduction method combining principal component analysis and Hotelling’s T^(2) and a multilayer convolutional bidirectional long short-term memory(MSC_BiLSTM)classifier model for network traffic intrusion detection.This method reduces the parameters and redundancy of the model by feature extraction and extracts the dependent features between the data by a bidirectional long short-term memory(BiLSTM)network,which fully considers the influence between the before and after features.The network traffic is first characteristically downscaled by principal component analysis(PCA),and then the downscaled principal components are used as input to Hotelling’s T^(2) to compare the differences between groups.For datasets with outliers,Hotelling’s T^(2) can help identify the groups where the outliers are located and quantitatively measure the extent of the outliers.Finally,a multilayer convolutional neural network and a BiLSTM network are used to extract the spatial and temporal features of network traffic data.The empirical consequences exhibit that the suggested approach in this manuscript attains superior outcomes in precision,recall and F1-score juxtaposed with the prevailing techniques.The results show that the intrusion detection accuracy,precision,and F1-score of the proposed MSC_BiLSTM model for the CIC-IDS 2017 dataset are 98.71%,95.97%,and 90.22%. 展开更多
关键词 network intrusion traffic detection PCA Hotelling’s T^(2) BiLsTM
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Evolution and Governance of the Structure of Marine Economic Networks in China’s Coastal Areas: Based on Sea-related A-share Listed Companies
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作者 LI Bo CAO Gai 《Chinese Geographical Science》 SCIE CSCD 2024年第5期899-916,共18页
Data on discrete,isolated attributes of the marine economy are often used in traditional marine economic research.However,as the focus of urban research shifts from internal static attributes to external dynamic linka... Data on discrete,isolated attributes of the marine economy are often used in traditional marine economic research.However,as the focus of urban research shifts from internal static attributes to external dynamic linkages,the importance of marine economic net-work research is beginning to emerge.The construction of the marine economic network in China’s coastal areas is necessary to change the flow of land and sea resources and optimize regional marine economic development.Employing data from headquarters and branches of sea-related A-share listed enterprises to construct the marine economic network in China,we use social network analysis(SNA)to discuss the characteristics of its evolution as of 2010,2015,and 2020 and its governance.The following results were obtained.1)In terms of topological characteristics,the scale of the marine economic network in China’s coastal areas has accelerated and expan-ded,and the connections have become increasingly close;thus,this development has complex network characteristics.2)In terms of spatial structure,the intensity of the connection fluctuates and does not form stable development support;the group structure gradually becomes clear,but the overall pattern is fragmented;there are spatial differences in marine economic agglomeration radiation;the radi-ation effect of the eastern marine economic circle is obvious;and the polarization effect of northern and southern marine economic circles is significant.On this basis,we construct a framework for the governance of a marine economic network with the market,the government,and industry as the three governing bodies.By clarifying the driving factors and building objectives of marine economic network construction,this study aims to foster the high-quality development of China’s marine economy. 展开更多
关键词 marine economic network sea-related A-share listed companies social network analysis(sNA) network governance China’s coastal areas
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Changes of China’s Status in the Global System and Its Influencing Factors:A Multiple Contact Networks Perspective
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作者 LIU Jian LIU Jibin +2 位作者 YANG Qingshan CAI Sikai LIU Jie 《Chinese Geographical Science》 SCIE CSCD 2024年第2期265-279,共15页
Clarifying China’s position in the global system is an important logical basis for developing national diplomacy.Although much research has been done on China’s development status,most studies have been based on cou... Clarifying China’s position in the global system is an important logical basis for developing national diplomacy.Although much research has been done on China’s development status,most studies have been based on country comparisons or institutional en-vironment.In today’s networked era in which the global economy,trade,personnel,and information are closely connected,studies on China’s global position and its status changes and influencing factors in multiple contact networks are still insufficient.In this study,from the perspective of diverse global contact networks,we constructed economic,cultural,and political influence indices to explore the changes and influencing factors on China’s status in the global system from 2005 to 2018.The results show that during the study period,China’s global influence in the fields of economic ties,cultural exchanges,and political contacts increased significantly,but its influ-ence in the fields of cultural exchanges and political contacts lagged far economic ties.The pattern of China’s economic influence on various economies around the world has shown a transformation from an‘upright pyramid’to an‘inverted pyramid’structure.The proportion of these economies in low-influence zones has decreased from more than 60%in 2005 to less than 20%in 2018.China’s cultural and political influence on various economies around the world has increased significantly;however,for the former,the percentage of high-influence areas is still less than 20%,whereas for the latter the percentage of these economies in medium-and high-influence areas is still less than 50%.Analyses such as a scatter plot matrix show that geographical proximity,economic globalization,close cooperation with developing countries,and a proactive and peaceful foreign policy are important factors in improving China’s status in the diverse global network system. 展开更多
关键词 global system economic ties cultural exchanges political contacts multiple contact networks China’s status
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A Spectral Convolutional Neural Network Model Based on Adaptive Fick’s Law for Hyperspectral Image Classification
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作者 Tsu-Yang Wu Haonan Li +1 位作者 Saru Kumari Chien-Ming Chen 《Computers, Materials & Continua》 SCIE EI 2024年第4期19-46,共28页
Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convol... Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm(AFLA-SCNN)is proposed.The Adaptive Fick’s Law Algorithm(AFLA)constitutes a novel metaheuristic algorithm introduced herein,encompassing three new strategies:Adaptive weight factor,Gaussian mutation,and probability update policy.With adaptive weight factor,the algorithmcan adjust theweights according to the change in the number of iterations to improve the performance of the algorithm.Gaussianmutation helps the algorithm avoid falling into local optimal solutions and improves the searchability of the algorithm.The probability update strategy helps to improve the exploitability and adaptability of the algorithm.Within the AFLA-SCNN model,AFLA is employed to optimize two hyperparameters in the SCNN model,namely,“numEpochs”and“miniBatchSize”,to attain their optimal values.AFLA’s performance is initially validated across 28 functions in 10D,30D,and 50D for CEC2013 and 29 functions in 10D,30D,and 50D for CEC2017.Experimental results indicate AFLA’s marked performance superiority over nine other prominent optimization algorithms.Subsequently,the AFLA-SCNN model was compared with the Spectral Convolutional Neural Network model based on Fick’s Law Algorithm(FLA-SCNN),Spectral Convolutional Neural Network model based on Harris Hawks Optimization(HHO-SCNN),Spectral Convolutional Neural Network model based onDifferential Evolution(DE-SCNN),SpectralConvolutionalNeuralNetwork(SCNN)model,and SupportVector Machines(SVM)model using the Indian Pines dataset and PaviaUniversity dataset.The experimental results show that the AFLA-SCNN model outperforms other models in terms of Accuracy,Precision,Recall,and F1-score on Indian Pines and Pavia University.Among them,the Accuracy of the AFLA-SCNN model on Indian Pines reached 99.875%,and the Accuracy on PaviaUniversity reached 98.022%.In conclusion,our proposed AFLA-SCNN model is deemed to significantly enhance the precision of hyperspectral image classification. 展开更多
关键词 Adaptive Fick’s law algorithm spectral convolutional neural network metaheuristic algorithm intelligent optimization algorithm hyperspectral image classification
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Habits on Social Networks at Workplace: A Survey of Motivations and Behaviour
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作者 Thomas Kakou Kouassi Douatia Koné +3 位作者 Aliou Bamba Aladji Kamagaté Olivier Asseu Yvon Kermarrec 《Open Journal of Applied Sciences》 2024年第8期2154-2168,共15页
This article explores the use of social networks by workers in Abidjan, Côte d’Ivoire, with particular emphasis on a descriptive or quantitative analysis aimed at understanding motivations and methods of use. Mo... This article explores the use of social networks by workers in Abidjan, Côte d’Ivoire, with particular emphasis on a descriptive or quantitative analysis aimed at understanding motivations and methods of use. More than five hundred and fifty questionnaires were distributed, highlighting workers’ preferred digital channels and platforms. The results indicate that the majority use social media through their mobile phones, with WhatsApp being the most popular app, followed by Facebook and LinkedIn. The study reveals that workers use social media for entertainment purposes and to develop professional and social relationships, with 55% unable to live without social media at work for recreational activities. In addition, 35% spend on average 1 to 2 hours on social networks, mainly between 12 p.m. and 2 p.m. It also appears that 46% believe that social networks moderately improve their productivity. These findings can guide marketing strategies, training, technology development and government policies related to the use of social media in the workplace. 展开更多
关键词 social network social Media Applications Poisson’s Law sTATIsTICs Digital supports Workers Productivity
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基于复杂网络的Braess悖论现象 被引量:4
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作者 刘巍 曾庆山 《计算机工程与设计》 北大核心 2015年第4期1098-1102,共5页
通过将复杂网络理论应用于城市交通中,分析当存在大量居民起讫点及路段时,城市交通中的Braess悖论现象。利用MATLAB建立一个双层城市交通网络,基于Braess悖论现象的成因,对城市交通网络进行交通配流;在此基础上,通过采用MATLAB对城市交... 通过将复杂网络理论应用于城市交通中,分析当存在大量居民起讫点及路段时,城市交通中的Braess悖论现象。利用MATLAB建立一个双层城市交通网络,基于Braess悖论现象的成因,对城市交通网络进行交通配流;在此基础上,通过采用MATLAB对城市交通流进行仿真,研究当改变路段实际通行能力、新增居民起讫点或路段时,城市交通网络中的Braess悖论现象,确定造成该现象的路段,提供改善城市交通的方案。 展开更多
关键词 复杂网络 城市交通 braess悖论 网络模型 仿真
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Braess模型与城市网络的空间复杂化探讨 被引量:4
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作者 陈彦光 刘继生 《地理科学》 CSCD 北大核心 2006年第6期658-663,共6页
B raess交通网络模型是经典的图论模型,但该模型同时具有很强的地理学色彩。B raess借助一个简单的网络揭示了出人意料的地理现象:增加交通路线有时反而降低运输效率。从理论地理学的角度对B raess网络进行了数学抽象,然后利用规划理论... B raess交通网络模型是经典的图论模型,但该模型同时具有很强的地理学色彩。B raess借助一个简单的网络揭示了出人意料的地理现象:增加交通路线有时反而降低运输效率。从理论地理学的角度对B raess网络进行了数学抽象,然后利用规划理论、图论和微分方程解析等方法揭示出区域-城市地理系统的空间复杂化两个重要动因:空间相互作用和宏观对称破坏。 展开更多
关键词 braess佯谬 空间复杂性 空间复杂化 对称破缺 空间相互作用
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NEURAL NETWORK SMITH PREDICTIVE CONTROL FOR TELEROBOTS WITH TIME DELAY 被引量:3
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作者 黄金泉 徐亮 Frank L Lewis 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2001年第1期35-40,共6页
A neural network Smith predictive control strategy is proposed to deal with inpu t and feedback time delays in telerobot systems. The delay time is assumed to b e invariant and unknown. The proposed control structure... A neural network Smith predictive control strategy is proposed to deal with inpu t and feedback time delays in telerobot systems. The delay time is assumed to b e invariant and unknown. The proposed control structure consists of a slave syst em and a master controller. In the slave system, a recurrent neural network (RNN ) with on-line weight tuning algorithm is employed to approximate the dynamics of the time-delay-free nonlinear plant, which is used to linearize the slave s ystem. The master controller is a Smith predictor for the linearized slave syste m, which provides prediction and maintains the desirable tracking performance. S tability propriety is guaranteed based on the Lyapunov method. A simulation of a two-link robotic manipulator is provided to illustrate the effectiveness of th e proposed control strategy. 展开更多
关键词 TELEROBOT time delay s ystem neural networks smith predictor
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地理学多视角研究方法——Braess网络车流分配过程的理论分析与数值计算 被引量:3
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作者 陈彦光 《地理研究》 CSCD 北大核心 2008年第6期1367-1380,共14页
对复杂的地理系统采用多种方法从不同的视角开展分析,可以降低错误结论的概率。本文以Braess交通网络为例,提出一个地理系统多视角分析的研究案例。首先借助La氏乘数法预测奇对称Braess网络的车流优化分配的结果。然后采用数值计算和模... 对复杂的地理系统采用多种方法从不同的视角开展分析,可以降低错误结论的概率。本文以Braess交通网络为例,提出一个地理系统多视角分析的研究案例。首先借助La氏乘数法预测奇对称Braess网络的车流优化分配的结果。然后采用数值计算和模拟方法论证,在该网络中,车流会通过自组织过程自动向着优化分配的方向演化,并且利用Markov链预测各个阶段的车流分配数值。最后借助最大熵原理从理论上证明,上述最优化过程的本质是地理系统的熵最大化;运用对偶规划和对称思想揭示,熵最大化的实质是车流运行的耗时总量最小。不同的方法给出的结果殊途同归、互相印证。这一套研究方法可以推广到多维不对称的交通网络,进而推广应用于地理学其他方面的理论分析和应用研究。 展开更多
关键词 地理研究方法 理论演绎 数值模拟 braess网络 最大熵方法
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城市路网设计中Braess诡异发生条件新析
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作者 邵敏华 孙立军 《长沙交通学院学报》 2008年第4期58-61,共4页
对城市道路网络设计中Braess诡异发生条件进行分析,指出Pas,Principio和Penchi-na的分析忽视了新增道路对相交道路路阻函数参数的影响,低估了Braess诡异出现的可能性.分析表明,在以城市交通网络为研究对象时,新增道路会带来相交道路自... 对城市道路网络设计中Braess诡异发生条件进行分析,指出Pas,Principio和Penchi-na的分析忽视了新增道路对相交道路路阻函数参数的影响,低估了Braess诡异出现的可能性.分析表明,在以城市交通网络为研究对象时,新增道路会带来相交道路自由流行程时间和拥挤时间的增加,而如将这一影响引入Braess诡异发生条件分析中时,Braess诡异出现的可能性将大大增加,应当在城市交通网络设计中引起重视. 展开更多
关键词 城市路网设计 braess诡异 路阻函数
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基于Network Service的WEB管理系统安全
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作者 苏啸 范晰 《萍乡高等专科学校学报》 2006年第3期5-8,共4页
随着Internet/Intranet技术的发展,基于B/S结构的Web管理系统成为开发研究的热点。因为Web应用程序允许用户访问中心资源(即Web服务器)并通过此中心资源访问其他资源(如数据库服务器),因此安全性是Web应用程序中一个关键部分。所以采取... 随着Internet/Intranet技术的发展,基于B/S结构的Web管理系统成为开发研究的热点。因为Web应用程序允许用户访问中心资源(即Web服务器)并通过此中心资源访问其他资源(如数据库服务器),因此安全性是Web应用程序中一个关键部分。所以采取严格的安全措施,为用户提供安全的环境,是Web管理系统开发管理中的重要举措。 展开更多
关键词 INTERNET/INTRANET network sERVICE B/s开发平台 安全
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拥挤交通网络的Braess’悖论现象 被引量:5
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作者 赵春雪 傅白白 王天明 《交通运输系统工程与信息》 EI CSCD 北大核心 2012年第4期155-160,共6页
在拥挤交通网络中,路段阻抗不仅与本路段车流量有关,也受其它路段车流量影响.本文讨论拥挤交通网络中同时考虑本路段和其它路段流量影响时Braess’悖论的性质及在系统最优分配下新增路段的作用.利用用户平衡(UE)和系统最优(SO)条件,计... 在拥挤交通网络中,路段阻抗不仅与本路段车流量有关,也受其它路段车流量影响.本文讨论拥挤交通网络中同时考虑本路段和其它路段流量影响时Braess’悖论的性质及在系统最优分配下新增路段的作用.利用用户平衡(UE)和系统最优(SO)条件,计算得出Braess’悖论发生时交通需求具体范围及SO分配下新增路段有意义的交通需求具体范围,研究其它路段车流量对悖论产生概率影响及对SO分配下新增路段是否起作用的影响,讨论其它路段对UE分配和SO分配网络总阻抗差距的影响.结果表明,悖论发生概率,SO分配下新增路段起作用的概率及两种交通分配网络总阻抗的差距都受其它路段不同程度的影响,这为城市交通网络规划拓宽了思路. 展开更多
关键词 城市交通 braess’悖论 解析方法 交通网络 用户平衡 系统最优
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在片S参数计量比对结果浅析
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作者 刘晨 高岭 +7 位作者 栾鹏 陈婷 黄英龙 李艳奎 金诚 邹喜跃 陆景 陈科元 《计量学报》 CSCD 北大核心 2024年第9期1401-1406,共6页
中国电子科技集团公司第十三研究所作为主导实验室开展了在片S参数计量比对工作,对参比实验室提交的在片S参数测量结果进行了汇总分析,并用E_n值对各参比实验室测量结果进行了评价。通过在片S参数计量比对,确保了量值传递的准确、可靠,... 中国电子科技集团公司第十三研究所作为主导实验室开展了在片S参数计量比对工作,对参比实验室提交的在片S参数测量结果进行了汇总分析,并用E_n值对各参比实验室测量结果进行了评价。通过在片S参数计量比对,确保了量值传递的准确、可靠,特别是对在片S参数测量不确定度的主要来源统一了认识。同时也为业内提供了在片S参数测量一致性的比较平台。 展开更多
关键词 无线电计量 在片s参数 计量比对 矢量网络分析仪
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基于D-S证据理论的农作物气候品质预测方法研究:以晚熟杂交柑橘春见为例
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作者 付世军 李梦 +6 位作者 杨晓兵 何震 袁佳阳 刘书慧 徐越 卢德全 张利平 《贵州农业科学》 CAS 2024年第5期122-132,共11页
【目的】基于多源气象数据构建果实品质(糖含量等级)预测模型,为科学评价果实气候品质及深入挖掘农产品气候资源提供科学依据。【方法】以晚熟柑橘春见果实为研究对象,利用多源数据融合技术、人工神经网络(BP神经网络、RBF神经网络和El... 【目的】基于多源气象数据构建果实品质(糖含量等级)预测模型,为科学评价果实气候品质及深入挖掘农产品气候资源提供科学依据。【方法】以晚熟柑橘春见果实为研究对象,利用多源数据融合技术、人工神经网络(BP神经网络、RBF神经网络和Elman神经网络)和D-S证据理论,包括气象数据质量控制、特征选取、特征级融合、决策级融合4个步骤,构建基于多源气象数据的果实品质(糖含量等级)预测模型。【结果】春见果实品质预测模型采用BP神经网络预测结果总体准确率为87.50%,平均绝对误差(MAE)为0.150,均方根误差(RMSE)为0.447;RBF神经网络预测结果总体准确率为85.00%,MAE为0.175,RMSE为0.474;Elman神经网络预测结果总体准确率为87.50%,MAE为0.150,RMSE为0.447;D-S证据理论决策融合总体预测准确率达95.20%,分别较BP神经网络、RBF神经网络和Elman神经网络提升7.7百分点、10.2百分点和7.7百分点,MAE和RMSE分别为0.040和0.214,均明显降低。【结论】D-S证据理论决策融合后的果实品质预测准确率相比单一神经网络预测更高、误差更小。 展开更多
关键词 晚熟柑橘 春见 气候品质 多源数据融合 BP神经网络 RBF神经网络 ELMAN神经网络 D-s证据理论
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基于ST-CNN的脉冲型地震动与脉冲周期融合识别方法
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作者 禹海涛 朱晨阳 +3 位作者 傅大宝 许乃星 卢哲超 蔡辉腾 《岩土工程学报》 EI CAS CSCD 北大核心 2024年第12期2675-2683,共9页
如何快速准确地识别脉冲型地震动是困扰学术界和工程界的关键难题,定量识别方法虽然能够克服人工识别的经验性限制,但是传统定量识别方法存在识别结果不一致、适用范围不广泛、难以同时识别脉冲周期或识别的脉冲周期部分情况下差异明显... 如何快速准确地识别脉冲型地震动是困扰学术界和工程界的关键难题,定量识别方法虽然能够克服人工识别的经验性限制,但是传统定量识别方法存在识别结果不一致、适用范围不广泛、难以同时识别脉冲周期或识别的脉冲周期部分情况下差异明显等问题。为此建立了一种问题针对性融合学习规则并结合卷积神经网络(CNN),开发出了一种新的脉冲型地震动与脉冲周期同步识别方法。该学习规则通过对基于不同识别原理的多个传统典型识别方法进行融合学习并采用全球范围的30000条任意方向地震动数据进行训练和验证,摒弃了以往繁琐的人工标记过程并得到了3个问题针对性识别模型,分别命名为Strict识别模型、General识别模型以及TP识别模型。除此之外,为解决地震动时序输入信息不足从而导致模型泛化能力较弱的问题,对CNN的输入结构进行了优化增强,提出了ST-CNN模型。其引入了S变换层以将地震动时序变换至时频,从而增加了频域分布信息并进一步提高了识别精度。结果表明:Strict识别模型能严格区分脉冲型与非脉冲型地震动,识别结果得到已有方法的一致认可;General识别模型的识别能力更强,适用范围更加广泛;TP识别模型识别的脉冲周期更加准确,并可与前述识别模型并用以同步输出识别结果。提出的问题针对性融合学习规则还可推广至其他工程领域与其他机器学习模型,建立的识别方法可为脉冲型地震动研究提供科学指导。 展开更多
关键词 脉冲型地震动 脉冲周期 识别方法 卷积神经网络 s变换
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Soft Computing of Biochemical Oxygen Demand Using an Improved T–S Fuzzy Neural Network 被引量:4
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作者 乔俊飞 李微 韩红桂 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2014年第Z1期1254-1259,共6页
It is difficult to measure the online values of biochemical oxygen demand(BOD) due to the characteristics of nonlinear dynamics, large lag and uncertainty in wastewater treatment process. In this paper, based on the k... It is difficult to measure the online values of biochemical oxygen demand(BOD) due to the characteristics of nonlinear dynamics, large lag and uncertainty in wastewater treatment process. In this paper, based on the knowledge representation ability and learning capability, an improved T–S fuzzy neural network(TSFNN) is introduced to predict BOD values by the soft computing method. In this improved TSFNN, a K-means clustering is used to initialize the structure of TSFNN, including the number of fuzzy rules and parameters of membership function. For training TSFNN, a gradient descent method with the momentum item is used to adjust antecedent parameters and consequent parameters. This improved TSFNN is applied to predict the BOD values in effluent of the wastewater treatment process. The simulation results show that the TSFNN with K-means clustering algorithm can measure the BOD values accurately. The algorithm presents better approximation performance than some other methods. 展开更多
关键词 BIOCHEMICAL oxygen DEMAND WAsTEWATER treatment T–s fuzzy NEURAL network K-MEANs clustering
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Evolution Characteristics of Government-Industry-University-Research Cooperative Innovation Network for China's Agriculture and Influ- encing Factors: Illustrated According to Agricultural Patent Case 被引量:14
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作者 LI Erling YAO Fei +1 位作者 XI Jiaxin GUO Chunyang 《Chinese Geographical Science》 SCIE CSCD 2018年第1期137-152,共16页
Under the special background of China, the cooperative innovation between different government-industry-university-research institutes plays an increasingly important role in the agricultural field. However, the exist... Under the special background of China, the cooperative innovation between different government-industry-university-research institutes plays an increasingly important role in the agricultural field. However, the existing literature has paid little attention to it. Considering the cooperation patents, published in the agriculture field stemming from the Full-text Database of China Patents as the study object, the spatial and institutional attribute of the authors as the data source, and by combining the social network and spatial econometrics analysis, this paper analyzes the structure evolution characteristics of cooperative innovation networks of agricultural government-industry-university-research institute in the city level of China in 1985–2014, based on the triple helix theory, with the influence factors discussed. This shows that, 1) since 1985, China's agricultural innovation level has been substantially increased, but the development degree of the cooperative innovation network is low, and the patent cooperation mainly relies on authors in the same unit; 2) enterprises play a leading role in the agricultural cooperative innovation. The effect of the government and hybrid organizations driven by the government is not obvious; 3) the cooperative innovation in the province and city dominates, and a multi-pole pattern has been formed. The cooperative innovation network structure evolves from a single helix empty core and double helix multi core to a double helix hierarchical network; 4) the city's science, education funding and personnel investment are key factors determining the agricultural cooperative innovation, while the agricultural development of the city presents slight negative impacts on it. The spatial mismatch of supply and demand is present in the technical cooperative innovation of China's agriculture. Therefore, the science enhancement and education investment to big agricultural provinces should be promptly implemented. 展开更多
关键词 cooperation innovation networks government-industry-university-research institute China's agricultural patent socialnetwork Analysis sNA)
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基于加权D-S证据理论的旋翼故障诊断
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作者 高亚东 张传壮 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2024年第1期66-75,共10页
旋翼作为直升机的升力面和操作面,其健康状态对直升机的安全至关重要。旋翼故障诊断技术仍是直升机健康与使用监测系统(Health and usage monitoring system, HUMS)领域的薄弱环节,开发旋翼故障诊断技术具有重要价值。基于信息融合技术... 旋翼作为直升机的升力面和操作面,其健康状态对直升机的安全至关重要。旋翼故障诊断技术仍是直升机健康与使用监测系统(Health and usage monitoring system, HUMS)领域的薄弱环节,开发旋翼故障诊断技术具有重要价值。基于信息融合技术,首先分析了旋翼故障的诊断机理,建立了旋翼故障模型,通过流固耦合仿真获取了不同故障下桨叶、轮毂和机身的故障特征信息,生成数据集进行网络训练和验证。然后,利用遗传算法反向传播(Genetic algorithm-backpropagation, GA-BP)优化神经网络诊断3种类型的直升机旋翼故障,即后缘调整片误调、变距拉杆误调和桨叶质量不平衡。3个逐级神经网络分别对旋翼故障类型、故障位置和故障程度进行了诊断识别。最后采用加权的Dempster-Shafer(D-S)证据理论对旋翼故障进行诊断和分析。结果证明基于改进D-S证据理论的旋翼故障诊断方法能够成功应用到旋翼故障诊断中,并具有良好的识别效果。 展开更多
关键词 旋翼系统 故障诊断 GA-BP神经网络 信息融合技术 D-s证据理论
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DETERMINING THE STRUCTURES AND PARAMETERS OF RADIAL BASIS FUNCTION NEURAL NETWORKS USING IMPROVED GENETIC ALGORITHMS 被引量:1
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作者 Meiqin Liu Jida Chen 《Journal of Central South University》 SCIE EI CAS 1998年第2期68-73,共6页
The method of determining the structures and parameters of radial basis function neural networks(RBFNNs) using improved genetic algorithms is proposed. Akaike′s information criterion (AIC) with generalization error t... The method of determining the structures and parameters of radial basis function neural networks(RBFNNs) using improved genetic algorithms is proposed. Akaike′s information criterion (AIC) with generalization error term is used as the best criterion of optimizing the structures and parameters of networks. It is shown from the simulation results that the method not only improves the approximation and generalization capability of RBFNNs ,but also obtain the optimal or suboptimal structures of networks. 展开更多
关键词 RADIAL BAsIs function NEURAL network GENETIC algorithms Akaike′s information CRITERION OVERFITTING
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Back propagation artificial neural network for community Alzheimer's disease screening in China 被引量:6
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作者 Jun Tang Lei Wu +6 位作者 Helang Huang Jiang Feng Yefeng Yuan Yueping Zhou Peng Huang Yan Xu Chao Yu 《Neural Regeneration Research》 SCIE CAS CSCD 2013年第3期270-276,共7页
AIzheimer's disease patients diagnosed with the Chinese Classification of Mental Disorders diagnostic criteria were selected from the community through on-site sampling. Levels of macro and trace elements were measur... AIzheimer's disease patients diagnosed with the Chinese Classification of Mental Disorders diagnostic criteria were selected from the community through on-site sampling. Levels of macro and trace elements were measured in blood samples using an atomic absorption method, and neurotransmitters were measured using a radioimmunoassay method. SPSS 13.0 was used to establish a database, and a back propagation artificial neural network for Alzheimer's disease prediction was simulated using Clementine 12.0 software. With scores of activities of daily living, creatinine, 5-hydroxytryptamine, age, dopamine and aluminum as input variables, the results revealed that the area under the curve in our back propagation artificial neural network was 0.929 (95% confidence interval: 0.868-0.968), sensitivity was 90.00%, specificity was 95.00%, and accuracy was 92.50%. The findings indicated that the results of back propagation artificial neural network established based on the above six variables were satisfactory for screening and diagnosis of Alzheimer's disease in patients selected from the community. 展开更多
关键词 neural regeneration clinical practice artificial neural network Alzheimer's disease MATHEMATICALMODEL COMMUNITY trace elements NEUROTRANsMITTERs grant-supported paper NEUROREGENERATION
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