Applications of knowledge-based programming to power engineering problems

1989 ◽  
Vol 4 (1) ◽  
pp. 345-352 ◽  
Author(s):  
T. Taylor ◽  
D. Lubkeman
Keyword(s):  
Power Engineering ◽  
Knowledge Based ◽  
Engineering Problems

Applications of wavelet transform on power engineering problems — A brief review

2017 ◽  
Vol 15 (03) ◽  
pp. 1730001
Author(s):  
Subramani Chinnamuthu ◽  
C. Vimala ◽  
A. A. Jimoh ◽  
Adedayo Ademola Yusuff
Keyword(s):  
Wavelet Transform ◽  
Power System ◽  
Review Paper ◽  
Power Engineering ◽  
System Stability ◽  
Engineering Research ◽  
Engineering Problems ◽  
Different Types ◽  
Power Measurements ◽  
Selection Of

The main scope of this paper is about the applications of wavelet transform (WT) on power engineering research. This review paper deals with the summary of applications of WT to different power system problems including transmission line faults detection, power quality issues, power forecasting, power measurements and power system stability. Different types of wavelet are used for the solution of various power engineering issues, and the selection of suitable wavelet for specific problems is also discussed in this paper with the support of literature.

scholarly journals Fuzzy Set Based Models and Methods of Decision Making and Power Engineering Problems

Engineering ◽  
2013 ◽  
Vol 05 (05) ◽  
pp. 41-51 ◽  
Author(s):  
Petr Ya. Ekel ◽  
Illya V. Kokshenev ◽  
Roberta O. Parreiras ◽  
Gladstone B. Alves ◽  
Paulo M. N. Souza
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Power Engineering ◽  
Engineering Problems

Integrating knowledge-based systems and artificial neural networks for engineering

1995 ◽  
Vol 9 (1) ◽  
pp. 13-22 ◽  
Author(s):  
Nabil Kartam ◽  
Ian Flood ◽  
Tanit Tongthong
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Generalized Solution ◽  
Knowledge Based Systems ◽  
Knowledge Based ◽  
Engineering Problems ◽  
Scope Of Application ◽  
Artificial Neural ◽  
The Individual

AbstractThe feasibility and relative merits of integrating knowledge-based systems (KBSs) and artificial neural networks (ANNs) for application to engineering problems are presented and evaluated. The strength of KBSs lies in their ability to represent human judgment and solve problems by providing explanations from and reasoning with heuristic knowledge. ANNs demonstrate problem solving characteristics not inherent in KBSs, including an ability to learn from example, develop a generalized solution applicable to a range of examples of the problem, and process information extremely rapidly. In this respect, KBSs and ANNs are complementary, rather than alternatives, and may be integrated into a system that exploits the advantages of both technologies. The scope of application and quality of solutions produced by such a hybrid extend beyond the boundaries of the individual technologies. This paper identifies and describes how KBSs and ANNs can be integrated, and provides an evaluation of the advantages that will accrue in engineering applications.

Sign in / Sign up

Export Citation Format

Share Document