@INPROCEEDINGS { Rsds4251,
author = {Wu, Xiaohong and Liang, Jiuzhen}, 
title = {Worm Harm Prediction Based on Segment Procedure Neural Networks}, 
booktitle = {Rough Sets and Knowledge Technology}, 
conference = {Rough Sets and Knowledge Technology}, 
series =  = {Lecture Notes in Computer Science}, 
volume = 4062, 
pages = {383--388}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
year = 2006, 
editor = {Wang, Guoying and Peters, James F. and Skowron, Andrzej and Yao, Yiyu}, 
isbn = {978-3-540-36297-5}, 
abstract = {This paper deals with the application of segment procedure neural networks to predict harm status of horsetail-pine worm. A novel procedure neural networks is proposed to solve those problems which are related to certain distinct segments of procedure. It is indicated that this model is a generalized form of the known procedure neural networks, and it owns all properties of the known model. This paper also presents learning algorithms for the segment procedure neural networks. Horsetail-pine worm forecast is a hard work for forest experts, but it is a typical segment procedure problem. In this paper a segment procedure neural networks is applied to deal with this issue, and some simulation experiment results are presented.}, 
keywords = {neural networks, topological structure, procedure neural networks, segment, algorithm, learning, prediction, }, 
}