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Application of PSO-Adaptive Neural-fuzzy Inference System (ANFIS) in Analog Circuit Fault Diagnosis

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6146))

Abstract

In order to solve the problem of fault diagnosis method for analog IC diagnosis, the method based on Adaptive Neural-fuzzy Inference System (ANFIS) is proposed. Using subtractive clustering and Particle Swarm Optimization (PSO)-hybrid algorithm as a tool for building the fault diagnosis model, then, the model of fault diagnosis system was used to the circuit fault diagnosis. Simulation results have shown that the method is more effective.

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© 2010 Springer-Verlag Berlin Heidelberg

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Zuo, L., Hou, L., Zhang, W., Geng, S., Wu, W. (2010). Application of PSO-Adaptive Neural-fuzzy Inference System (ANFIS) in Analog Circuit Fault Diagnosis. In: Tan, Y., Shi, Y., Tan, K.C. (eds) Advances in Swarm Intelligence. ICSI 2010. Lecture Notes in Computer Science, vol 6146. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13498-2_7

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  • DOI: https://doi.org/10.1007/978-3-642-13498-2_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13497-5

  • Online ISBN: 978-3-642-13498-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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