DocumentCode :
2207990
Title :
Sequential learning neural network and its application in agriculture
Author :
Deng, Chao ; Xiong, FanLun ; Tan, Ying ; He, Zhenya
Author_Institution :
Univ. of Sci. & Technol. of China, Hefei, China
Volume :
1
fYear :
1998
fDate :
4-8 May 1998
Firstpage :
221
Abstract :
We propose a sequential learning neural network (SLNN) and analyze the learning and recognition performances of the SLNN. The proposed SLNN consists of the bounded weight adjustment algorithm and structure adjustment method. Through many experiments, it turns out that our proposed SLNN can not only learn the knowledge of samples in series efficiently but also has fast learning speed. As an actual example of our network we have succeeded in applying our SLNN to Asian corn borer forecasting
Keywords :
agriculture; learning (artificial intelligence); neural nets; Asian corn borer forecasting; agriculture; bounded weight adjustment algorithm; fast learning speed; recognition performances; sequential learning neural network; structure adjustment method; Agriculture; Chaos; Feedforward neural networks; Feedforward systems; Helium; Intelligent networks; Learning systems; Neural networks; Performance analysis; Production;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
ISSN :
1098-7576
Print_ISBN :
0-7803-4859-1
Type :
conf
DOI :
10.1109/IJCNN.1998.682266
Filename :
682266
Link To Document :
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