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Time series forecasting is usually limited to one-step ahead prediction. This goal is extended here to longer-term prediction, obtained using the least-square support vector machines model. The influence of the model parameters is observed when the time horizon of the prediction is increased and for various prediction methods. The model selection to(More)
An optical method for synthesizing a binary matrix representing all feasible solutions of a bounded ͑input length restricted͒ NP-complete combinatorial problem is presented. After the preparation of this matrix, an optical matrix-vector multiplier can be used in order to multiply the synthesized binary matrix and a grayscale vector representing the weights(More)
This paper introduces an optical solution to (bounded-length input instances of) an NP-complete problem called the traveling salesman problem using a pure optical system. The solution is based on the multiplication of a binary-matrix, representing all feasible routes, by a weight-vector, representing the weights of the problem. The multiplication of the(More)
The double vector quantization forecasting method based on Kohonen self-organizing maps is applied to predict the missing values of the CATS competition data set. As one of the features of the method is the ability to predict vectors instead of scalar values in a single step, the compromise between the size of the vector prediction and the number of(More)
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