期刊文献+
共找到6篇文章
< 1 >
每页显示 20 50 100
短跑运动能力的神经网络评价方法 被引量:10
1
作者 陈海英 郭巧 徐力 《北京理工大学学报》 EI CAS CSCD 北大核心 2003年第1期54-57,共4页
选取形态、机能、素质、心理、技术等 15项指标构成百米跑人体运动能力评价指标体系 ,结合 10 0名 12~2 0岁青少年的各项测试指标及专家对其运动能力的综合评价结果 ,建立了基于神经网络的百米跑运动能力评价模型 .将各项测试指标归一... 选取形态、机能、素质、心理、技术等 15项指标构成百米跑人体运动能力评价指标体系 ,结合 10 0名 12~2 0岁青少年的各项测试指标及专家对其运动能力的综合评价结果 ,建立了基于神经网络的百米跑运动能力评价模型 .将各项测试指标归一化作为网络输入 ,专家的评价结果作为网络输出 ,对训练好的模型进行验证 ,结果令人满意 .神经网络方法克服了现有专家评分方法的不足 ,为运动员选材领域提供了一种新的参数模型 . 展开更多
关键词 短跑运动 人体运动能力 百米跑 运动员选材 神经网络评价方法 能力评价 指标体系
下载PDF
沥青路面使用性能的神经网络评价方法
2
作者 吴锡蛟 颜强 《上海公路》 2002年第3期2-5,共4页
沥青路面使用性能指标之间存在着内在的关联性,但这种高度非线性关系无法用传统的统计回归方法建立数学模型。本文采用神经网络方法建立了路面破损状况与其它指标之间的模型,并采用实测数据进行了检验,结果表明,模型的精度可满足工程实... 沥青路面使用性能指标之间存在着内在的关联性,但这种高度非线性关系无法用传统的统计回归方法建立数学模型。本文采用神经网络方法建立了路面破损状况与其它指标之间的模型,并采用实测数据进行了检验,结果表明,模型的精度可满足工程实践的要求。 展开更多
关键词 沥青路面 使用性能 神经网络评价方法 数学模型
下载PDF
电力系统传输网络危险源评价方法研究
3
作者 刘敏 《信息记录材料》 2018年第11期238-239,共2页
安全生产是电力系统稳定运行的重要前提,对其存在的危险源进行评价有助于及时排除电力系统传输网络中的危险因素。在传统网络危险源评价方法的基础上,提出RBF神经网络评价方法。同时,阐述了此评价方法的评价流程,以及构建安全评价模型... 安全生产是电力系统稳定运行的重要前提,对其存在的危险源进行评价有助于及时排除电力系统传输网络中的危险因素。在传统网络危险源评价方法的基础上,提出RBF神经网络评价方法。同时,阐述了此评价方法的评价流程,以及构建安全评价模型并求解,在实际应用中证明了其实用性和精确性。 展开更多
关键词 RBF神经网络评价方法 电力系统 网络危险源 安全评价模型
下载PDF
Ecosystem Health Assessment of Honghu Lake Wetland of China Using Artificial Neural Network Approach 被引量:21
4
作者 MO Minghao WANG Xuelei +3 位作者 WU Houjian CAI Shuming Xiaoyang ZHANG WANG Huiliang 《Chinese Geographical Science》 SCIE CSCD 2009年第4期349-356,共8页
Honghu Lake,located in the southeast of Hubei Province,China,has suffered a severe disturbance during the past few decades.To restore the ecosystem,the Honghu Lake Wetland Protection and Restoration Demonstration Proj... Honghu Lake,located in the southeast of Hubei Province,China,has suffered a severe disturbance during the past few decades.To restore the ecosystem,the Honghu Lake Wetland Protection and Restoration Demonstration Project(HLWPRDP) has been implemented since 2004.A back propagation(BP) artificial neural network(ANN) approach was applied to evaluatinig the ecosystem health of the Honghu Lake wetland.And the effectiveness of the HLWPRDP was also assessed by comparing the ecosystem health before and after the project.Particularly,12 ecosystem health indices were used as evaluation parameters to establish a set of three-layer BP ANNs.The output is one layer of ecosystem health index.After training and testing the BP ANNs,an optimal model of BP ANNs was selected to assess the ecosystem health of the Honghu Lake wetland.The result indicates that four stages can be identified based on the change of the ecosystem health from 1990 to 2008 and the ecosystem health index ranges from morbidity before the implementation of HLWPRDP(in 2002) to middle health after the implementation of the HLWPRDP(in 2005).It demonstrates that the HLWPRDP is effective and the BP ANN could be used as a tool for the assessment of ecosystem health. 展开更多
关键词 ecosystem health artificial neural network wetland restoration Honghu Lake
下载PDF
Researches On The Network Security Evaluation Method Based Bn BP Neural Network
5
作者 Zhang Yibin Yan Zequan 《International Journal of Technology Management》 2014年第9期93-95,共3页
This paper first describes the basic theory of BP neural network algorithm, defects and improved methods, establishes a computer network security evaluation index system, explores the computer network security evaluat... This paper first describes the basic theory of BP neural network algorithm, defects and improved methods, establishes a computer network security evaluation index system, explores the computer network security evaluation method based on BP neural network, and has designed to build the evaluation model, and shows that the method is feasible through the MATLAB simulation experiments. 展开更多
关键词 BP neural network network security MODEL EVALUATION
下载PDF
A Credit Risk Evaluation Approach to Neural Network Training by Means of Financial Ratios
6
作者 Qian Ye 《Journal of Systems Science and Information》 2009年第1期23-32,共10页
In recent years artificial neural networks are used to recognize the risk category of investigated companies. The research is based on data from 81 listed enterprises that applied for credit in domestic regional banks... In recent years artificial neural networks are used to recognize the risk category of investigated companies. The research is based on data from 81 listed enterprises that applied for credit in domestic regional banks operating in China. The backpropagation algorithm-the multilayer feedforward network structure is described. Each firm is described by 9 diagnostic variables and potential borrowers are classified into four classes. The efficiency of classification is evaluated in terms of classification errors calculated from the actual classification made by the credit officers. The results of the experiments show that LevenbergMarque training error is smallest among 4 learning algorithms and its performance is better, and application of artificial neural networks and classification functions can support the creditworthiness evaluation of borrowers. 展开更多
关键词 credit risk evaluation financial ratio neural network classification algorithms the multilayer network
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部