The Role Of Artificial Neural Network Enhancing Predication for the Relation Between Financial Performance and Environmental and Social Responsibility Disclosure Index.

Esraa ElBatanoni, Mohamed Elrakaiby
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Abstract

The Researcher aimed in this Research Is to Test the Effect Of Artificial Intelligence Tools, Represented By Artificial Neural Networks, On The Accuracy Of Improving The Prediction Accuracy Of The Relationship Between Financial Performance And The Indicator Of Disclosure Of Environmental And Social Responsibility For Egyptian Companies. Through A Sample Of 72 Egyptian listed Companies, The Researcher Reached the Ability Of Multilayer percepton with one hidden layer network for Artificial Neural Networks In Explaining The Relationship Between Financial Performance. The Environmental and Social Responsibility Is Accurately Disclosed, And The T-Test for CPU Training Time Proves That All Classifiers Have Proven to Have Significantly Lower CPU Time (Data Processing Speed) For This Model After Using Artificial Intelligence Tools. Which Indicates the Importance and Efficiency Of The Model Using Artificial Neural Networks In Interpreting The Relationship between Financial Performance And The Indicator Of Disclosure Of Environmental And Social Responsibility For Egyptian Companies.
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人工神经网络对财务业绩与环境和社会责任信息披露指数之间关系的增强预测作用。
本研究旨在测试以人工神经网络为代表的人工智能工具对提高埃及公司财务业绩与环境和社会责任披露指标之间关系预测准确性的影响。通过对 72 家埃及上市公司的抽样调查,研究人员发现人工神经网络的多层感知器和一个隐藏层网络能够解释财务业绩与环境和社会责任之间的关系。环境和社会责任得到了准确披露,CPU 训练时间的 T 检验证明,在使用人工智能工具后,所有分类器的 CPU 时间(数据处理速度)都明显缩短。这表明使用人工神经网络的模型在解释埃及公司的财务业绩与环境和社会责任披露指标之间的关系方面具有重要意义和效率。
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