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      Simulation of superconductive fault current limiter (SFCL) using modular neural networks

      , Article IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics, Paris, 6 November 2006 through 10 November 2006 ; 2006 , Pages 4415-4419 ; 1424401364 (ISBN); 9781424401369 (ISBN) Makki, B ; Sadati, N ; Sohani, M ; Sharif University of Technology
      2006
      Abstract
      Modular Neural Networks have had significant success in a wide range of applications because of their superiority over single non-modular ones in terms of proper data representation, feasibility of hardware implementation and faster learning. This paper presents a constructive multilayer neural network (CMNN) in conjunction with a Hopfield model using a new cost function to simulate the behavior of superconductive fault current limiters (SFCLs). The results show that the proposed approach can efficiently simulate the behavior of SFCLs. ©2006 IEEE  
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