Hybrid soft computing systems: industrial and commercial applications

Author

Bonissone, Piero P. ; Chen, Yu-To ; Goebel, Kai ; Khedkar, Pratap S.

Author_Institution

Gen. Electr. Corp. Res. & Dev. Center, Niskayuna, NY, USA

Volume

87

Issue

9

fYear

1999

fDate

9/1/1999 12:00:00 AM

Firstpage

1641

Lastpage

1667

Abstract

Soft computing (SC) is an association of computing methodologies that includes as its principal members fuzzy logic, neurocomputing, evolutionary computing and probabilistic computing. We present a collection of methods and tools that can be used to perform diagnostics, estimation, and control. These tools are a great match for real-world applications that are characterized by imprecise, uncertain data and incomplete domain knowledge. We outline the advantages of applying SC techniques and in particular the synergy derived from the use of hybrid SC systems. We illustrate some combinations of hybrid SC systems, such as fuzzy logic controllers (FLCs) tuned by neural networks (NNs) and evolutionary computing (EC), NNs tuned by EC or FLCs, and EC controlled by FLCs. We discuss three successful real-world examples of SC applications to industrial equipment diagnostics, freight train control, and residential property valuation

Keywords

case-based reasoning; evolutionary computation; fault diagnosis; forecasting theory; fuzzy logic; intelligent control; neural nets; railways; estimation; freight train control; fuzzy logic controllers; hybrid soft computing systems; imprecise uncertain data; incomplete domain knowledge; industrial equipment diagnostics; neurocomputing; probabilistic computing; residential property valuation; Automatic control; Computer industry; Computer networks; Condition monitoring; Control systems; Cost accounting; Electrical equipment industry; Fuzzy logic; Industrial control; Neural networks;

fLanguage

English

Journal_Title

Proceedings of the IEEE

Publisher

ieee

ISSN

0018-9219

Type

jour

DOI

10.1109/5.784245

Filename

784245