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

页码：35 / 42

页数：8

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