Wavelets to Enhance Computational Intelligence in Computer-Aided Engineering

• Authors: Hojjat Adeli
• Venue: Proceedings of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering
• Year: 2006

Concurrent engineering (CE) is intertwined with the field of computer-aided engineering (CAE). The author presents a vision of future for CE and CAE where computational intelligence (CI) will play an increasingly significant role. Various disciplines within CE such as design, manufacturing, knowledge management, collaborative computing, Web processes and services, and distributed infrastructures must rely heavily on CI to achieve the increasing sophistication demand. The author has been advocating and advancing a multi-paradigm approach for solution of complicated and noisy computational intelligence problems. In 1995 he co-authored Machine Learning --Neural Networks, Genetic Algorithms, and Fuzzy Systems [1] the first authored book that presented and integrated the three principal soft computing and computational intelligence approaches. It was shown that such integration would provide a more powerful approach than any of the three approaches used individually. Since the publication of that ground-breaking book the author and his associates have demonstrated that chaos theory and wavelets can be used to further enhance computational intelligence especially for complicated and noisy pattern recognition problems. In this lecture it is shown how wavelets can be used as a powerful tool to complement and enhance other soft computing techniques such as neural networks and fuzzy logic as well as the chaos theory for solution of complicated and seemingly intractable CI problems. Examples of research performed by the author and his research associates in the areas of intelligent transportation systems [2--4], vibrations control [5--8], and nonlinear system identification [9--10] are presented.