@article {doi:10.1002/isaf.1409,
	title = {Time series forecasting using evolutionary neural nets implemented in a volunteer computing system},
	journal = {Intelligent Systems in Accounting, Finance and Management},
	volume = {24},
	number = {2-3},
	year = {2017},
	pages = {87-95},
	abstract = {Summary jsEvRBF is a time-series forecasting method based on genetic algorithm and neural nets. Written in JavaScript language, can be executed in most web browsers. Consequently, everybody can participate in the experiments, and scientists can take advantage of nowadays available browsers and devices as computation environments. This is also a great challenge as the language support and performance varies from one browser to another. In this paper, jsEvRBF has been tested in a volunteer computing experiment, and also in a single-browser one. Both experiments are related to forecasting currencies exchange, and the results show the viability of the proposal.},
	keywords = {evolutionary computation, fintech, radial basis function neural networks, time-series forecasting, volunteer computation, Web-based programming},
	doi = {10.1002/isaf.1409},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/isaf.1409},
	author = {Rivas, V.M. and E. Parras-Guti{\'e}rrez and Merelo, J.J. and Arenas, M.G. and Garc{\'\i}a-Fern{\'a}ndez, P.}
}
@conference {10.1007/978-3-319-40111-9_5,
	title = {Web Browser-Based Forecasting of Economic Time-Series},
	booktitle = {Decision Economics, In Commemoration of the Birth Centennial of Herbert A. Simon 1916-2016 (Nobel Prize in Economics 1978)},
	year = {2016},
	pages = {35{\textendash}42},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {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.},
	isbn = {978-3-319-40111-9},
	author = {Rivas, V. M. and E. Parras-Guti{\'e}rrez and Merelo, J. J. and Arenas, M. G. and Garc{\'\i}a-Fern{\'a}ndez, P.},
	editor = {Bucciarelli, Edgardo and Silvestri, Marcello and Rodr{\'\i}guez Gonz{\'a}lez, Sara}
}
