| 人工神经网络的建设工期定额地域分类 |
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| 引用本文： | 张云波,胡云昌.人工神经网络的建设工期定额地域分类[J].华侨大学学报(自然科学版),2004,25(3):270-274. |
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| 作者姓名： | 张云波 胡云昌 |
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| 作者单位： | 华侨大学土木工程系,福建,泉州,362011;天津大学建筑工程学院,天津,300072 |
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| 基金项目： | 福建省自然科学基金资助项目 (E9910 0 2 6 ) |
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| 摘 要： | 对影响建设工程工期的因素进行分析．根据各地区不同的自然建设条件，对全国31个省的省会城市的自然条件列为输入矢量．应用自组织竞争网络的聚类功能、Matlab 6．1软件编程和2～9类区分法，分别划分出建设工期定额的地域类别．通过对计算成果的分析，提出按4类划分建设工程工期定额的地域分类方法．它能区分不同地区自然建设条件的差异，使工期定额的制定更加合理．
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| 关 键 词： | 自组织神经网络 工期定额 地域类别 聚类分析 |
| 文章编号： | 1000-5013(2004)03-0270-05 |
Regionally Categorize the Working-Day Norm of Construction Work by Applying Artficial Neural Network |
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| Abstract: | The factors influencing construction period are analysed. The natural conditions of 31 provincial capitals in our country are listed as input vectors according to different natural conditions of construction in various regions. On this basis, the regional category of working day norm of construction is divided respectively by applying the clustering function of self organizing competitive networks and Matlab 6.1 software programming and 2~9 category division. After analysing the reckoning, the author puts forward a regional 4 category division for categorizing working day norm of construction work. By which the regional differences in natural conditions of construction can be distinguished, and the formulation of working day norm can be even more reasonable. |
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| Keywords: | self-organizing neural networks working-day norm regional category cluster analysis |
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