%0 Conference Paper %1 DBLP:conf/waim/ZuoTLYC04 %A Zuo, Jie %A Tang, Changjie %A Li, Chuan %A an Yuan, Chang %A long Chen, An %B Advances in Web-Age Information Management: 5th International Conference, WAIM 2004 %C Dalian, China %D 2004 %E Li, Qing %E Wang, Guoren %E Feng, Ling %I Springer %K Data Processing Series Time algorithms, expression gene genetic programming, %P 55--64 %T Time Series Prediction Based on Gene Expression Programming %U http://springerlink.metapress.com/openurl.asp?genre=article&issn=0302-9743&volume=3129&spage=55 %V 3129 %X 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. %@ 3-540-22418-1

@inproceedings{DBLP:conf/waim/ZuoTLYC04, 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.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Dalian, China}, author = {Zuo, Jie and Tang, Changjie and Li, Chuan and an Yuan, Chang and long Chen, An}, bibsource = {DBLP, http://dblp.uni-trier.de}, biburl = {https://www.bibsonomy.org/bibtex/272530b9ae63d5ff27088b5ecf81fc618/brazovayeye}, booktitle = {Advances in Web-Age Information Management: 5th International Conference, WAIM 2004}, editor = {Li, Qing and Wang, Guoren and Feng, Ling}, interhash = {15daab01ddc2968821fd1e265ed52029}, intrahash = {72530b9ae63d5ff27088b5ecf81fc618}, isbn = {3-540-22418-1}, keywords = {Data Processing Series Time algorithms, expression gene genetic programming,}, month = {15-17 July}, notes = {Computer Science Department, Sichuan University, Chengdu, Sichuan, China, 610065}, pages = {55--64}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, timestamp = {2008-06-19T17:56:01.000+0200}, title = {Time Series Prediction Based on Gene Expression Programming}, url = {http://springerlink.metapress.com/openurl.asp?genre=article&issn=0302-9743&volume=3129&spage=55}, volume = 3129, year = 2004 }