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A proposed model for comparing the performance of neural network and statistical approaches in predicting project profits of an asphalt paving company

机译:用于比较神经网络性能和统计方法以预测沥青摊铺公司项目利润的拟议模型

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Summary form only given, as follows. It is assumed that the performance of a model for predicting project profits of an asphalt paving company varies with an unknown number of parameters (Berry, 1990). Present models such as neural networks and advanced statistical approaches have been promoted as being capable of augmenting, or even supplanting, human decision-making. Yet, little research published to date compares the results of these two different models (Caudill, 1990). Few published works establish any criteria for evaluating the results provided by these models (Cohen and Howe, 1988). It is the authors' belief that neural network models must be subjected to the same rigorous quantitative and qualitative evaluation that statistical models have been subject to.
机译:仅给出摘要表格,如下。假设预测沥青路面公司项目利润的模型的性能会随着未知数量的参数而变化(Berry,1990)。诸如神经网络和高级统计方法之类的现有模型已经得到了推广,因为它们能够增强甚至取代人类的决策能力。然而,迄今发表的研究很少比较这两种不同模型的结果(Caudill,1990)。很少有已发表的著作为评估这些模型提供的结果建立任何标准(Cohen and Howe,1988)。作者认为,神经网络模型必须接受与统计模型相同的严格的定量和定性评估。

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