| 基于神经网络的学生党员考核评价系统的开发 |
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| 引用本文： | 林继熙,颜桂梅.基于神经网络的学生党员考核评价系统的开发[J].福建农林大学学报(哲学社会科学版),2012,15(6):93-97. |
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| 作者姓名： | 林继熙 颜桂梅 |
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| 作者单位： | 1. 福建农林大学蜂学学院
2. 福建农林大学金山学院,福建福州,350002 |
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| 基金项目： | 福建省教育厅基金课题(JB11099S);福建农林大学党建项目(KX1120011) |
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| 摘 要： | 为了高效率、低成本地评价高校学生党员的综合素质,采用BP神经网络技术,开发了学生党员考棱评价系统.该神经网络使用专家提供的100组数据进行训练,训练结果的相对误差为0.4％,采用20组非训练数据进行检验,相对误差为0％.实践表明,即使专家的评价规则很复杂,无法用数学模型直观表达,神经网络也能够仿真专家的思维逻辑,对党员素质进行公平、公正的评价.
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| 关 键 词： | 学生党员 神经网络 综合素质 评价系统 |
Development of student Party members assessment system based on neural network |
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| LIN Ji-xi
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YAN Gui-mei.Development of student Party members assessment system based on neural network[J].Journal of Fujian Agriculture and Forestry University,2012,15(6):93-97. |
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| Authors: | LIN Ji-xi YAN Gui-mei |
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| Institution: | 1.College of Bee Science,Fujian Agriculture and Forestry University; 2.Jinshan College,Fujian Agriculture and Forestry University,Fuzhou,Fujian 350002,China) |
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| Abstract: | For assessment of college student Party members comprehensive quality in high effect and low cost.back propagation neural network technology has been applied to develop student Party members assessment system.In the neural network,100 sets of data offered by the experts are used for training,and the relative error of result is 0.4%,meanwhile the 20 sets of non-training data are used for check and the relative error is 0%.It has been proved that the neural network is able to simulate the experts thinking logic and conduct a fair assessment of student Party members' quality,even if the experts' appraisal rules are complicated and can not be illustrated intuitively by mathematical model. |
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| Keywords: | student Party members neural network comprehensive quality assessment system |
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