Integrating knowledge-based systems and artificial neural networks for engineering

The feasibility and relative merits of integrating knowledge-based systems (KBSs) and artificial neural networks (ANNs) for application to engineering problems are presented and evaluated. The strength of KBSs lies in their ability to represent human judgment and solve problems by providing explanations from and reasoning with heuristic knowledge. ANNs demonstrate problem solving characteristics not inherent in KBSs, including an ability to learn from example, develop a generalized solution applicable to a range of examples of the problem, and process information extremely rapidly. In this respect, KBSs and ANNs are complementary, rather than alternatives, and may be integrated into a system that exploits the advantages of both technologies. The scope of application and quality of solutions produced by such a hybrid extend beyond the boundaries of the individual technologies. This paper identifies and describes how KBSs and ANNs can be integrated, and provides an evaluation of the advantages that will accrue in engineering applications.

[1]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[2]  Sema E. Alptekin,et al.  Integrating scheduling and control functions in computer integrated manufacturing using artificial intelligence , 1989 .

[3]  P. F. Spelt,et al.  Hybrid Intelligent Perception System: Intelligent perception through combining Artificial Neural Networks and an Expert System , 1990 .

[4]  J. J. Ferrada,et al.  Hybrid system for fault diagnosis using scanned input: A tutorial , 1991 .

[5]  Hecht-Nielsen Theory of the backpropagation neural network , 1989 .

[6]  Tarek Hegazy,et al.  Neural networks as tools in construction , 1991 .

[7]  Ian Flood,et al.  Neural Networks in Civil Engineering. I: Principles and Understanding , 1994 .

[8]  Ting-Peng Liang,et al.  A composite approach to inducing knowledge for expert systems design , 1992 .

[9]  Nabil A. Kartam,et al.  Expert systems in construction engineering and management: state of the art , 1990, Knowl. Eng. Rev..

[10]  I. A. Macleod Artificial intelligence techniques and applications for civil and structural engineers: Edited by B.V.H. Topping Civil Comp Press , 1991 .

[11]  George M. Whitson,et al.  Using an artificial neural system to determine the knowledge based of an expert system , 1990, SIGSMALL '90.

[12]  Soundar Kumara,et al.  Neuroform—Neural Network System for Vertical Formwork Selection , 1992 .

[13]  Kanaan A. Faisal,et al.  Rule-Based Training of Neural Networks , 1991 .

[14]  Juan J. Ferrada,et al.  Applications of neural networks in chemical engineering: Hybrid systems , 1990 .

[15]  Li-Chen Fu,et al.  Mapping rule-based systems into neural architecture , 1990, Knowl. Based Syst..

[16]  Ian Flood,et al.  Neural networks in civil engineering. II: Systems and application , 1994 .

[17]  Jennifer Ace A neural net/ES hybrid , 1992 .

[18]  Paul Bourgine,et al.  Extracting legal knowledge by means of a multilayer neural network application to municipal jurisprudence , 1991, ICAIL '91.