Title :
Application of Improved Logarithm Logistic Models in Population Prediction
Author :
Bin Li ; Tianfei Wang ; Liping Jia
Author_Institution :
Lab. of Intell. Inf. Process. & Applic., Leshan Normal Univ., Leshan, China
Abstract :
In this paper, improved Logistic models are given, which are called Logarithm Logistic Models. Based on U.S. Census data, the parameters of the models were estimated by applying the Least Squares Method. The experiments show that the prediction value of the new models is much closer to the actual value than the classical Logistic model. Finally, through analyzing the rationality of the maximum population capacity, the trend of Logistic curves and the rationality of prediction value, the most appropriate model is recommended.
Keywords :
demography; least squares approximations; prediction theory; classical logistic model; improved logarithm logistic models; least squares method; logistic curves; maximum population capacity; population prediction; prediction value rationality; Biological system modeling; Computational modeling; Logistics; Mathematical model; Predictive models; Sociology; Statistics; growth rate; logarithm logistic model; logistic model; population prediction;
Conference_Titel :
Computational Intelligence and Security (CIS), 2012 Eighth International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4673-4725-9
DOI :
10.1109/CIS.2012.30