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T h i s p a p e r p r e s e n t s t h e development and maintenance o f i n t e l l i g e n t ' s w i t c h i n g sequence generat i o n ' s y s t e m s . The a u t h o r ' s h a v e d e v e l o p e d a new framework which can c o n s t r u c t a n d u p d a t e i t s knowledge b a s e without e x t e r n a l i n f l u e n c e . T h i s p a p e r proposes an a u t o m a t i c knowledge a c q u i s i t i o n method, a key p a r t of

Tokyo Electric Power Company (TEPCO) 1-410, Irifune, C h u e k u , Tokyo 104 JAPAN ogiQaisun. tepco.co.jp . AbstractThe paper presents an artificial neural network(ANN) approach to 5 diagnostic system for a Gas Insulated Switchgear(G1S). Firstly We survey the status of operational experience of failures in GISs and its diagnostic techniques. Secondly we present how t o acquire signal samples from the GIS and how to process them so as to be provided for an input layer of ANN. Finally we propose decision-tree like network referred to as Module Neural Network(MNN) through the comparison with well-known three-layered network as Straight Forward Neural Network(SFNN).

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