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Author Skomorokhov, Alexander O.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Abstract The paper considers Adaptive Learning Networks (ALN) as a tool to solve the problems of modeling, prediction, diagnostics and pattern recognition in complex systems. This method is similar to the neural network technique. The main difference is the self-organization of network structure on the basis of generation and estimation of various nodes, connections and weights. A set of functions presented in the paper shows that ALNs are easily realized in APL2. User-defined operators are used as a very convenient tool for ALN programming. The paper discusses the application of implemented software to the problem of Burnout Heat Flux Prediction in nuclear reactors. It is shown that ALN technique allows the prediction of burnout heat flux with approximately three times better accuracy than other commonly used methods.
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1988-12-01
Publisher Place New York
Journal ACM SIGAPL APL Quote Quad (APLQ)
Volume Number 24
Issue Number 1
Page Count 11
Starting Page 219
Ending Page 229

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Source: ACM Digital Library