Title :
Prediction Model in Statistics Data Based on Improved Cluster and Neural Network
Author :
Wang Zuo ; Sun Wenwen ; Li Jingyong ; Wang Zhe
Author_Institution :
Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
Abstract :
This paper presents a new prediction model, which combines the clustering with neural network. The existed clustering algorithm has the shortcoming that can not determine the clustering number K, so this paper combines it with the concept of rough set to improve, and tests it on the IRIS data, Then this paper presents the new forecasting model which combines improved clustering algorithm and neural networks to improve the prediction accuracy more effectively, and tests it in statistics data.
Keywords :
data handling; forecasting theory; neural nets; pattern clustering; rough set theory; statistics; IRIS data; clustering algorithm; forecasting model; neural network; prediction model; rough set; statistics data; Approximation algorithms; Approximation methods; Brain modeling; Clustering algorithms; Data models; Prediction algorithms; Predictive models; Cluster; K-means; Neural network; Prediction; Rough set;
Conference_Titel :
Intelligent System Design and Engineering Application (ISDEA), 2012 Second International Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-1-4577-2120-5
DOI :
10.1109/ISdea.2012.634
