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