从改进的影响和复杂性看人工神经网络在完备性预测中的贡献

Jaouad Maqboul, Bouchaib Bounabat Jaouad
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引用次数: 1

摘要

技术的发展和大量的数据产生,流通到公司,使得这些数据,公司的真正资本,损害了客户。错误的数据破坏了与客户的关系,公司必须解决这个问题,并确定它必须努力的高质量项目。在本文中,我们将介绍一种基于定性和定量分析的方法,以帮助决策者通过过程改进的影响和复杂性来确定目标数据。定性研究将是一个调查和定量研究,从调查数据中学习,以确定预测和数据的完整性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Contribution of Artificial Neural Network in Predicting Completeness Through the Impact and Complexity of its Improvement
The technological evolution and the immensity of the data produced, circulated into company makes these data, the real capital of the companies to the detriment of the customers. The erroneous data put the knockout to relationships with customers, the company must address this problem and identify the quality projects on which it must make an effort. In this article, we will present an approach based on qualitative and quantitative analysis to help the decision-makers to target data by its impacts and complexities of process improvement. The Qualitative study will be a survey and a quantitative to learn from survey data to decide the prediction and the completeness of data.
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