基于平衡计分卡和人工神经网络的IT部门绩效评估模型

Yurong Zeng, Lin Wang, Yonggang Wang
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引用次数: 1

摘要

在这个不断变化的世界中,信息技术(IT)部门的功能变得越来越重要。摘要本研究旨在建构一种基于平衡计分卡与人工神经网路的制造业资讯科技部门绩效评估方法。将一种新的基于混合粒子群优化(HPSO)的学习方法应用于人工神经网络。通过实例验证了人工神经网络模型的可靠性。结果表明,采用HPSO算法学习的神经网络模型具有较高的准确率,优于反向传播算法。实证结果表明,人工神经网络模型可以作为IT部门绩效评估的一种有说服力的分析工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Model for Evaluating Performance of IT Department based on Balanced Scorecard and Artificial Neural Network Approach
In this ever-changing world, the function of information technology (IT) department is becoming increasingly important. The objective of this study is to construct an approach based on balanced scorecard (BSC) and artificial neural network (ANN) for evaluating an IT department in the manufacturing industry. A novel hybrid particle swarm optimization (HPSO)-based learning method is utilized in the ANN. The reliability of the ANN model is tested by a practical example. The results show that the ANN model learned by HPSO algorithm has relative high accuracy and is better than the back propagation algorithm. The empirical findings suggest that the ANNs model can be a persuasive analytical tool for the performance evaluation of the IT department.
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