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The knowledge modeling system of ready-mixed concrete enterprise and artificial intelligence with ANN-GA for manufacturing production

机译:基于ANN-GA的预拌混凝土企业和人工智能的知识建模系统。

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摘要

Based on the characteristics of ready-mixed concrete enterprises, this paper puts forward that knowledge management (KM) is an effective way to contribute to enterprise production and operation. The knowledge content and relevant models of concrete enterprises are proposed, including advanced enterprise management, decision support for production operation, production and operation cost, and marketing-customer relationship. Afterwards knowledge contents are divided into static, strategic and reasoning knowledge. Besides knowledge unified expression is put forward accordingly. In addition, the KM system for process ready-mixed concrete enterprises management is established to facilitate effective production processing. As part of exploratory study, artificial neural network coupled with genetic algorithm (ANN-GA) as knowledge mining technology is applied in KM system to predict the 28-day compressive strength in concrete enterprises. The results shows that compared to back-propagation artificial neural network, the convergence rate of ANN-GA algorithm has been significantly improved and almost all the relative errors of predicted compressive strength of concrete C30 are within 3 %. It not only confirms the validity of the models, but also proves that ANN-GA algorithm is an effective knowledge mining method applied in concrete industry.
机译:结合混凝土企业的特点,提出知识管理是促进企业生产经营的有效途径。提出了具体企业的知识内容和相关模型,包括先进的企业管理,生产经营的决策支持,生产经营成本,市场与客户的关系。然后将知识内容分为静态知识,战略知识和推理知识。除了知识,还提出了统一表达。此外,建立了用于过程预拌混凝土企业管理的KM系统,以促进有效的生产过程。作为探索性研究的一部分,在知识管理系统中将人工神经网络与遗传算法(ANN-GA)结合作为知识挖掘技术,用于预测混凝土企业的28天抗压强度。结果表明,与反向传播人工神经网络相比,ANN-GA算法的收敛速度得到了显着提高,并且混凝土C30的预测抗压强度的几乎所有相对误差都在3%以内。它不仅证实了模型的有效性,而且证明了ANN-GA算法是一种在混凝土行业中有效的知识挖掘方法。

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