DocumentCode :
495559
Title :
Scissors Branch Algorithms Application in Platform of Milk Cow Disease Diagnose Expert System Pronunciation
Author :
Li-shu, Wang ; Guang-lin, Yang ; Zai-hua, Li ; Chang-li, Zhang
Author_Institution :
Northeast Agric. Univ., Harbin, China
Volume :
4
fYear :
2009
fDate :
March 31 2009-April 2 2009
Firstpage :
680
Lastpage :
682
Abstract :
Agricultural informationization is a main trend in agricultural development. Expert system (ES) is a capable assistant during agricultural production. However, now most country areas were not able to use the ES at all, it had influenced and restricted the development of the agricultural informationization seriously. This paper proposed a solution of voice service system of ES, which is suitable for peasant´s information transmission, especially the peasants from remote regions could obtain knowledge from ES by the voice service system. Aimed at the disadvantage of massive data of knowledge base and slow deduction, the system adopted the classification method based on decision tree, designed pruning algorithm and cut down the unrelated knowledge to the users in query course, therefore, before the inference engine deduced the knowledge asked by users, the structure of the decision tree had been simplified, so the speed of deduction was accelerated.
Keywords :
agriculture; decision trees; diagnostic expert systems; agricultural informationization; classification method; decision tree; milk cow disease diagnose expert system pronunciation; pruning algorithm; scissors branch algorithm; voice service system; Acceleration; Algorithm design and analysis; Classification tree analysis; Dairy products; Decision trees; Diagnostic expert systems; Diseases; Engines; Inference algorithms; Production systems; Disease Diagnose; Expert System; Pronunciation; Scissors Branch Algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
Type :
conf
DOI :
10.1109/CSIE.2009.546
Filename :
5171082
Link To Document :
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