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ECONOMIC BENEFIT EVALUATION OF INDUSTRIAL ENTERPRISES BASED ON BP NEURAL NETWORK OPTIMIZATION ALGORITHM

机译:基于BP神经网络优化算法的工业企业经济效益评价

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摘要

The economic evaluation methods of existing industrial enterprises have many limitations. In this paper, an economic benefit evaluation method of industrial enterprises based on BP neural network optimization algorithm is proposed. This method takes the economic indicators of enterprises as input of artificial neural network, and uses the optimized BP neural network model to evaluate and analyze enterprises. The running time is greatly shortened, and the evaluation results are objective and accurate. An example is given to illustrate the implementation of the method. The example shows the feasibility of the method. In the fast-changing market situation, the sustainable development of enterprises has attracted the attention of all sectors of society and has become the focus of research. The sustainable development of the enterprise is the objective requirement of the sustainable development of the economy, the guarantee for the long-term economic benefit of the enterprise, and the fundamental method and way to realize the long-term development of the enterprise. Therefore, for enterprises, sustainable development is the primary task of enterprises. The research on sustainable development of enterprises has become a hot topic in the practice and theory field of enterprise management. However, there has been no effective and systematic theory on the index system, quantification and evaluation methods of the evaluation of the sustainable development of enterprises.
机译:现有工业企业的经济评估方法有很多限制。本文提出了基于BP神经网络优化算法的工业企业经济效益评价方法。这种方法将企业的经济指标作为人工神经网络的输入,并利用优化的BP神经网络模型来评估和分析企业。运行时间大大缩短,评估结果是客观准确的。给出示例以说明方法的实现。该示例显示了该方法的可行性。在不断变化的市场形势中,企业的可持续发展引起了社会各界的关注,已成为研究的重点。企业的可持续发展是经济可持续发展的客观要求,保证企业长期经济利益,以及实现企业长期发展的基本方法和方法。因此,为企业而言,可持续发展是企业的主要任务。企业可持续发展研究已成为企业管理实践和理论领域的热门话题。但是,对企业可持续发展评估的指标体系,量化和评估方法没有有效和系统的理论。

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