Ventsislav Nikolov
ABSTRACT
In this paper an approach is proposed for associating priorities to the data according to their actuality and using of local neural network forecasting method. For this purpose modified learning rules are derived that lead to shifting of the prototype vectors in the self-organizing map and weighted training in the multilayer perceptron. This method is generally applicable to the forecasting of long and complex time series.
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- Nikolov, V. Optimizations in Time Series Clustering and Prediction. International Conference on Computer Systems and Technologies CompSysTech'10, Sofia, Bulgaria, June 17--18, 2010, pp. 528--533. Google ScholarDigital Library
- Pavlidis, N. G., V. P. Plagianakos, D. K. Tasoulis, M. N. Vrahatis. Financial Forecasting through Unsupervised Clustering and Neural Networks. Operational Research: An International Journal, Vol. 6, No. 2, 2006, pp. 103--127.Google ScholarCross Ref
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Index Terms
- Local weighted approach to time series forecasting
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