標題: | A Xerion-based Perl program to train a neural network for grid pattern recognition |
作者: | Kao, JJ 交大名義發表 環境工程研究所 National Chiao Tung University Institute of Environmental Engineering |
關鍵字: | neural network;grid pattern;Digital Elevation Model;drainage pattern |
公開日期: | 1-十一月-1996 |
摘要: | Neural network training with the back propagation algorithm is an important artificial intelligence technique for grid pattern recognition. The training is time-consuming however and generally requires a trial-and-error procedure to configure the network. A Perl program executed with Xerion is presented to relieve the;training burden. Statistical reports such as computation time, learning performance, and validation performance are generated automatically by the program. A case study applying the program for training networks to determine a drainage pattern from Digital Elevation Model data is demonstrated and discussed. Manually determining drainage patterns from topographical maps for a grid-based model is tedious and subjective. The neural network has a self-learning capability that can replace human judgment involved in the conventional approach. Copyright (C) 1996 Elsevier Science Ltd. |
URI: | http://dx.doi.org/10.1016/S0098-3004(96)00042-8 http://hdl.handle.net/11536/968 |
ISSN: | 0098-3004 |
DOI: | 10.1016/S0098-3004(96)00042-8 |
期刊: | COMPUTERS & GEOSCIENCES |
Volume: | 22 |
Issue: | 9 |
起始頁: | 1033 |
結束頁: | 1049 |
顯示於類別: | 期刊論文 |