Input selection for ANFIS learning
- 23 December 2002
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
[[abstract]]We present a quick and straightfoward way of input selection for neuro-fuzzy modeling using adaptive neuro-fuzzy inference systems (ANFIS). The method is tested on two real-world problems: the nonlinear regression problem of automobile MPG (miles per gallon) prediction, and the nonlinear system identification using the Box and Jenkins gas furnace data.[[fileno]]2030226030022[[department]]資訊工程學This publication has 10 references indexed in Scilit:
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