Time Series Prediction Based on Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{DBLP:conf/waim/ZuoTLYC04,

• author = "Jie Zuo and Changjie Tang and Chuan Li and Chang-an Yuan and An-long Chen",
• title = "Time Series Prediction Based on Gene Expression Programming",
• booktitle = "Advances in Web-Age Information Management: 5th International Conference, WAIM 2004",
• year = "2004",
• pages = "55--64",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• editor = "Qing Li and Guoren Wang and Ling Feng",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• volume = "3129",
• ISBN = "3-540-22418-1",
• address = "Dalian, China",
• month = "15-17 " # jul,
• keywords = "genetic algorithms, genetic programming, gene expression programming, Time Series Data Processing",
• DOI = "doi:10.1007/978-3-540-27772-9_7",
• abstract = "Two novel methods for Time Series Prediction based on GEP (Gene Expression Programming). The main contributions include: (1) GEP-Sliding Window Prediction Method (GEP-SWPM) to mine the relationship between future and historical data directly. (2) GEP-Differential Equation Prediction Method (GEP-DEPM) to mine ordinary differential equations from training data, and predict future trends based on specified initial conditions. (3) A brand new equation mining method, called Differential by Microscope Interpolation (DMI) that boosts the efficiency of our methods. (4) A new, simple and effective GEP-constants generation method called Meta-Constants (MC) is proposed. (5) It is proved that a minimum expression discovered by GEP-MC method with error not exceeding delta/2 uses at most log3(2L/delta) operators and the problem to find delta-accurate expression with fewer operators is NP-hard. Extensive experiments on real data sets for sun spot prediction show that the performance of the new method is 20-900 times higher than existing algorithms.",
• notes = "Computer Science Department, Sichuan University, Chengdu, Sichuan, China, 610065",

}

Genetic Programming entries for Jie Zuo Changjie Tang Chuan Li Chang-an Yuan An-long Chen

Citations