Developing a sugar-cane breeding assistant system by a hybrid adaptive learning technique

Author

Jiang, Mon-Fong ; Wang, Ching-Hung ; Tseng, Shian-Shyong

Author_Institution

Dept. of Comput. & Inf. Sci., Nat. Chiao Tung Univ., Hsinchu, Taiwan

Volume

2

fYear

1996

fDate

14-17 Oct 1996

Firstpage

1196

Abstract

The traditional sugar-cane breeding process depends on the determination of an experienced breeding researcher. Since the sugar-cane breeding problem in agriculture field is a complex one, the use of computer-aided methodology is very suitable to solve this problem. In this paper, we use the techniques of neural networks and genetic algorithms to construct a method in order to induce the sugar-cane cross model from the sugar-cane parent database established by the Taiwan Sugar Research Institute since 1990. The experimental results show that the correct percentage for testing is about 70%

Keywords

adaptive systems; agriculture; backpropagation; expert systems; feedforward neural nets; genetic algorithms; learning systems; Taiwan Sugar Research Institute; adaptive learning; agriculture; backpropagation; computer-aided methodology; genetic algorithms; multilayer neural networks; sugar-cane breeding assistant system; sugar-cane cross model; Agriculture; CADCAM; Computer aided instruction; Computer aided manufacturing; Databases; Genetic algorithms; Humans; Information science; Neural networks; Sugar industry;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1996., IEEE International Conference on

Conference_Location

Beijing

ISSN

1062-922X

Print_ISBN

0-7803-3280-6

Type

conf

DOI

10.1109/ICSMC.1996.571278

Filename

571278