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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
computer science
A hybrid forecasting model for enrollments based on aggregated fuzzy time series and particle swarm optimization
Expert Systems with Applications, Volume 38, No. 7, Year 2011
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Description
In this paper, a new forecasting model based on two computational methods, fuzzy time series and particle swarm optimization, is presented for academic enrollments. Most of fuzzy time series forecasting methods are based on modeling the global nature of the series behavior in the past data. To improve forecasting accuracy of fuzzy time series, the global information of fuzzy logical relationships is aggregated with the local information of latest fuzzy fluctuation to find the forecasting value in fuzzy time series. After that, a new forecasting model based on fuzzy time series and particle swarm optimization is developed to adjust the lengths of intervals in the universe of discourse. From the empirical study of forecasting enrollments of students of the University of Alabama, the experimental results show that the proposed model gets lower forecasting errors than those of other existing models including both training and testing phases. © 2011 Elsevier Ltd. All rights reserved.
Authors & Co-Authors
Huang, Yaolin
Taiwan, Taipei
National Taiwan University of Science and Technology
Horng, Shi Jinn
Taiwan, Taipei
National Taiwan University of Science and Technology
China, Chengdu
Xihua University
China, Chengdu
Southwest Jiaotong University
He, Mingxing
China, Chengdu
Xihua University
Fan, Pingzhi
China, Chengdu
Southwest Jiaotong University
Kao, Tzong Wann
Taiwan, Taipei
Taipei City University of Science and Technology
Khan, Muhammad Khurram
Saudi Arabia, Riyadh
King Saud University
Lai, Juilin
Taiwan, Miao-li
National United University Taiwan
Kuo, I. Hong
Taiwan, Taipei
Mackay Medicine, Nursing and Management College Taiwan
Statistics
Citations: 92
Authors: 8
Affiliations: 7
Identifiers
Doi:
10.1016/j.eswa.2010.12.127
ISSN:
09574174