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

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