An improvement Logistic model based on multiple objective genetic algorithm

• Published in: 2009 International Conference on Machine Learning and Cybernetics Vol. 4; pp. 2292 - 2295
• Main Author: Xiao-Yong Liu
• Format: Conference Proceeding
• Language: English
• 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
• ISBN: 9781424437023; 1424437024
• ISSN: 2160-133X
• DOI: 10.1109/ICMLC.2009.5212196

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.