出版社：Japan Society for Fuzzy Theory and Intelligent Informatics
摘要：In this paper, modellng technique is proposed. This modeling technique is based on concept of "soft computing". "soft computing" is an information processing technique for aiming at tractability, robustness, and low solution cost, by exploiting the tolerance for imprecision and avoiding the pursuit of excess precision. It is different from a conventional technique that uses elaborate algorithm and complex mathematical principle model. From this viewpoint, we also advocated an original modeling technique with reference for the process of vision cognitior, and have tried some application. The flow of this technique is as follows: at flrst transposes the characteristic of an object system to two or more ambiguous 2-dimensional geometric pattem information, transforms those pattems by leaming, finally combines them by the fuzzy technique, and performs the modeling of an object system. This technique was created by reference from the process of vision cognition: Detection of more global feature from local feature, and the parallelism of a lot of information expression and processing. We are calling this technique Pattern Infiormation Based Active Leaming Method (PBALM). PBALM have no mathematical formula and complicated algorithm, but just based only on simple operation. Moreover, as mentioned above, since it resolves object system into simple pattem information and treats as long as it is expressible by the patterrn, it can respond to large nonlinearity (robustness), Ieaming can also be performed with the intelligible form of modification of the pattem (tractability), and generally, there is little number of times of learning (low solution cost). In this paper, the idea of PBALM and the characteristic are described first. And the model of the air-conditioning jet wind velocity characteristic which is a nonlinear system is built. And it is shown that highly precise modeling is performed. Furthermore, the control problem of an inverted pendulum is taken up and it is shown that an effective control rule can be gained by PBALM using human's control data.
