基于模块化神经网络模型的高等学校资产管理绩效综合评价

Comprehensive Evaluation of College Assets Management Performance Based on a Modular Neural Network Model

对75所高校提供的各指标原始数据,通过层次分析法确定各评价指标权重、建立模块化神经网络模型、并利用交叉验证法挑选模型,对75所高校进行资产管理绩效综合评价,并与单一神经网络模型的正确率进行比较,发现模块化神经网络模型正确率较高,且模型结果合理。

Based on the raw data of each index provided by 75 colleges and universities, determines the weight of each evaluation index by AHP, establishes a modular neural network model, and uses the cross validation method to select the model to evaluate the performance of 75 colleges and universities. Compared with the single neural network model, finds that the modular neural network model is more accurate and the model is reasonable.