Web Browser-Based Forecasting of Economic Time-Series

被引:1
作者
Rivas, V. M. [1 ,3 ]
Parras-Gutierrez, E. [1 ]
Merelo, J. J. [2 ,3 ]
Arenas, M. G. [2 ,3 ]
Garcia-Fernandez, P. [2 ,3 ]
机构
[1] Univ Jaen, Dept Comp Sci, Campus Las Lagunillas S-N, Jaen 23071, Spain
[2] SPAIN Univ Granada, Dept Comp Architecture, Dept Technol, Dept Elect Tecnol ,Dept comp, Granada 18071, Spain
[3] GeNeura Team, Granada, Spain
来源
DECISION ECONOMICS, IN COMMEMORATION OF THE BIRTH CENTENNIAL OF HERBERT A. SIMON 1916-2016 (NOBEL PRIZE IN ECONOMICS 1978) | 2016年 / 475卷
关键词
Time-series forecasting; Evolutionary computation; Radial Basis Function Neural Networks; Web-based programming; Volunteer computation;
D O I
10.1007/978-3-319-40111-9_5
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper presents the implementation of a time series forecasting algorithm, jsEvRBF, that uses genetic algorithm and neural nets in a way that can be run in must modern web browsers. Using browsers to run forecasting algorithms is a challenge, since language support and performance varies across implementations of the JavaScript virtual machine and vendor. However, their use will provide a boost in the number of platforms available for scientists. jsEvRBF is written in JavaScript, so that it can be easily delivered to and executed by any device containing a web-browser just accessing an URL. The experiments show the results yielded by the algorithm over a data set related to currencies exchange. Best results achieved can be effectively compared against previous results in literature, though robustness of the new algorithm has to be improved.
引用
收藏
页码:35 / 42
页数:8
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