An improvement Logistic model based on multiple objective genetic algorithm

Logistic model is one of the classic models for predicting the number of literatures in a special field. This paper studies the logistic model that is used to describe literatures' increasing trend, analyzes the shortcoming of improvement algorithms of logistic model at present, and proposes a...

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Bibliographic Details
Published in2009 International Conference on Machine Learning and Cybernetics Vol. 4; pp. 2292 - 2295
Main Author Xiao-Yong Liu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
Algorithm design and analysis
Computer science
Cybernetics
Digital Library
Genetic Algorithm
Genetic algorithms
Logistic Model
Logistics
Machine learning
Mathematical model
Mathematics
Predictive models
Software libraries
The rule of literatures' increasing
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Summary:Logistic model is one of the classic models for predicting the number of literatures in a special field. This paper studies the logistic model that is used to describe literatures' increasing trend, analyzes the shortcoming of improvement algorithms of logistic model at present, and proposes a new algorithm, named DGA-logistic algorithm that is based on multiple objective genetic algorithm. For validating the new algorithm, this paper chooses Chinese digital library's literatures, which are published in recent years, as dataset. The numerical experiment showed that DGA-logistic has better forecasting result than improvement algorithms of logistic model at present.
ISBN:9781424437023
1424437024
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212196