DocumentCode :
478066
Title :
Evaluating the Agricultural Information Degree Using a Novel Genetic Algorithm
Author :
Liu, Zhibin ; Shen, Peng
Author_Institution :
Dept. of Econ. & Manage., North China Electr. Power Univ., Baoding
Volume :
1
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
593
Lastpage :
596
Abstract :
The agricultural information level is on the initial stage in Hebei province, so we should pay more attention to its construction. And on this basis we can find out the influencing factors and corresponding countermeasures. In order to evaluate the agricultural information degree scientifically and accurately, this paper proposes the optimal model based on improved genetic algorithm. The model has the advantages of self-learning, self-organizing and self-adapting, avoids the subjective mistakes in the evaluation process, and improves the evaluating accuracy greatly. The evaluation of 5 cities in Hebei Province shows that the results given by this model are reliable, and this method to evaluate the agricultural information level is feasible.
Keywords :
agriculture; genetic algorithms; Hebei province; agricultural information degree; improved genetic algorithm; Analysis of variance; Biological cells; Cities and towns; Computational biology; Evolution (biology); Genetic algorithms; Investments; Power generation economics; Statistics; Synchronous generators; Agricultural information degree; Comprehensive evaluation; Improved genetic algorithm; Indices system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
Type :
conf
DOI :
10.1109/ICNC.2008.6
Filename :
4666914
Link To Document :
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