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|Title:||On interpretation of graffiti commands for eBooks using a neural network and an improved genetic algorithm|
|Source:||The 10th IEEE International Conference on Fuzzy Systems : meeting the grand challenge : machines that serve people : The University of Melbourne, Australia, December, 2001, Sunday 2nd to Wednesday 5th, p. 1464-1467 How to cite?|
|Abstract:||This paper presents the interpretation of graffiti commands for Electronic Books (eBooks). The interpretation process is achieved by training a proposed neural network (NN) with link switches using an improved genetic algorithm (GA). By introducing the switches to the links, the proposed NN can learn the optimal network structure automatically. The structure and the parameters of the NN are tuned by the improved GA, which is implemented by floating point numbers. The processing time of the improved GA is shorter as reflected by some benchmark test functions. Simulation results on interpreting graffiti commands for eBooks using the proposed NN with link switches and the improved GA will be shown.|
|Rights:||© 2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
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|Appears in Collections:||Conference Paper|
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Checked on Dec 4, 2016
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