Application of SVR with improved ant colony optimization algorithms in exchange rate forecasting

Wei-Mou Hung; Wei-Chiang Hong

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Displaying similar documents to “Application of SVR with improved ant colony optimization algorithms in exchange rate forecasting”

Learning from imprecise examples with GA-P algorithms.

Luciano Sánchez, Inés Couso (1998)

Mathware and Soft Computing

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GA-P algorithms combine genetic programming and genetic algorithms to solve symbolic regression problems. In this work, we will learn a model by means of an interval GA-P procedure which can use precise or imprecise examples. This method provides us with an analytic expression that shows the dependence between input and output variables, using interval arithmetic. The method also provides us with interval estimations of the parameters on which this expression depends. The...

Hybrid approach to design optimisation: preserve accuracy, reduce dimensionality

Mariusz Kamola (2007)

International Journal of Applied Mathematics and Computer Science

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The paper proposes a design procedure for the creation of a robust and effective hybrid algorithm, tailored to and capable of carrying out a given design optimisation task. In the course of algorithm creation, a small set of simple optimisation methods is chosen, out of which those performing best will constitute the hybrid algorithm. The simplicity of the method allows implementing ad-hoc modifications if unexpected adverse features of the optimisation problem are found. It is postulated...

Adaptive prediction of stock exchange indices by state space wavelet networks

Mietek A. Brdyś, Adam Borowa, Piotr Idźkowiak, Marcin T. Brdyś (2009)

International Journal of Applied Mathematics and Computer Science

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The paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a state space wavelet network model of the index price. The approach can be applied to the development of tools for predicting changes of other economic indicators, especially stock exchange indices. The paper presents a general state space wavelet network model and the underlying principles. The model is applied to produce one session ahead and five sessions ahead adaptive predictors of the...

The dynamic linear model: An application to flood forecasting.

M. A. GÓMEZ-VILLEGAS and J. TEJADA E. G. SÁNCHEZ-MANZANO (1999)

Revista de la Real Academia de Ciencias Exactas Físicas y Naturales

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A neural-network controlled dynamic evolutionary scheme for global molecular geometry optimization

Anna Styrcz, Janusz Mrozek, Grzegorz Mazur (2011)

International Journal of Applied Mathematics and Computer Science

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A novel, neural network controlled, dynamic evolutionary algorithm is proposed for the purposes of molecular geometry optimization. The approach is tested for selected model molecules and some molecular systems of importance in biochemistry. The new algorithm is shown to compare favorably with the standard, statically parametrized memetic algorithm.

New machine learning methods for prediction of protein secondary structures

Jacek Błażewicz, Piotr Łukasik, Szymon Wilk (2007)

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A comparative evaluation of medium- and large-scale feature selectors for pattern classifiers

Mineichi Kudo, Jack Sklansky (1998)

Kybernetika

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Needs of feature selection in medium and large problems increases in many fields including medical and image processing fields. Previous comparative studies of feature selection algorithms are not satisfactory in problem size and in criterion function. In addition, no way has not shown to compare algorithms with different objectives. In this study, we propose a unified way to compare a large variety of algorithms. Our results show that the sequential floating algorithms promises for...