In this article, two models of the forecast of time series obtained from the chaotic dynamic syst... more In this article, two models of the forecast of time series obtained from the chaotic dynamic systems are presented: the Lorenz system, the manufacture system, and the volume of the Great Salt Lake of Utah. The theory of the nonlinear dynamic systems indicates the capacity of making good-quality predictions of series coming from dynamic systems with chaotic behavior up to a temporal horizon determined by the inverse of the major Lyapunov exponent. The analysis of the Fourier power spectrum and the calculation of the maximum Lyapunov exponent allow confirming the origin of the series from a chaotic dynamic system. The delay time and the global dimension are employed as parameters in the models of forecast of artificial neuronal networks (ANN) and support vector machine (SVM). This research demonstrates how forecast models built with ANN and SVM have the capacity of making forecasts of good quality, in a superior temporal horizon at the determined interval by the inverse of the maximum...
The aim of this paper is to development a very strong cryptographic systems using hyperelliptic C... more The aim of this paper is to development a very strong cryptographic systems using hyperelliptic Curves and Complete Synchronization for a Bidirectional Chaotic systems based on Lorenz attractor. Also performance sim- ulations of SISO and MIMO systems over fading channels produce a benet of 16dB for BER=10 e 6 once the
Page 1. A Fuzzy Decision Making Model for Determining Company Profile in Allocation of Public Fun... more Page 1. A Fuzzy Decision Making Model for Determining Company Profile in Allocation of Public Funding for Industrial Development Projects MIGUEL D. ALFARO, JUAN M. SEPÚLVEDA, CARLO A. CASORZO Department of ...
The aim of this paper is to make a contribution to the development of the new stronger cryptograp... more The aim of this paper is to make a contribution to the development of the new stronger cryptographic algorithm using chaotic systems and hyperelliptic curve. In this context, the Diffie-Hellman scheme is implemented with chaotic systems and ElGamal ...
IFIP Advances in Information and Communication Technology, 2015
ABSTRACT The price of copper and its variations represent a very important financial issue for mi... more ABSTRACT The price of copper and its variations represent a very important financial issue for mining companies and for the Chilean government because of its impact on the national economy. The price of commodities such as copper is highly volatile, dynamic and troublous. Due to this, forecasting is very complex. Using publicly data from October 24th of 2013 to August 29th of 2014 a multivaried based model using meta-heuristic optimization techniques is proposed. In particular, we use Genetic Algorithms and Simulated Annealing in order to find the best fitting parameters to forecast the variation on the copper price. A non-parametric test proposed by Timmermann and Pesaran is used to demonstrate the forecasting capacity of the models. Our numerical results show that the Genetic Algorithmic approach has a better performance than Simulated Annealing, being more effective for long range forecasting.
In this article, two models of the forecast of time series obtained from the chaotic dynamic syst... more In this article, two models of the forecast of time series obtained from the chaotic dynamic systems are presented: the Lorenz system, the manufacture system, and the volume of the Great Salt Lake of Utah. The theory of the nonlinear dynamic systems indicates the capacity of making good-quality predictions of series coming from dynamic systems with chaotic behavior up to a temporal horizon determined by the inverse of the major Lyapunov exponent. The analysis of the Fourier power spectrum and the calculation of the maximum Lyapunov exponent allow confirming the origin of the series from a chaotic dynamic system. The delay time and the global dimension are employed as parameters in the models of forecast of artificial neuronal networks (ANN) and support vector machine (SVM). This research demonstrates how forecast models built with ANN and SVM have the capacity of making forecasts of good quality, in a superior temporal horizon at the determined interval by the inverse of the maximum...
The aim of this paper is to development a very strong cryptographic systems using hyperelliptic C... more The aim of this paper is to development a very strong cryptographic systems using hyperelliptic Curves and Complete Synchronization for a Bidirectional Chaotic systems based on Lorenz attractor. Also performance sim- ulations of SISO and MIMO systems over fading channels produce a benet of 16dB for BER=10 e 6 once the
Page 1. A Fuzzy Decision Making Model for Determining Company Profile in Allocation of Public Fun... more Page 1. A Fuzzy Decision Making Model for Determining Company Profile in Allocation of Public Funding for Industrial Development Projects MIGUEL D. ALFARO, JUAN M. SEPÚLVEDA, CARLO A. CASORZO Department of ...
The aim of this paper is to make a contribution to the development of the new stronger cryptograp... more The aim of this paper is to make a contribution to the development of the new stronger cryptographic algorithm using chaotic systems and hyperelliptic curve. In this context, the Diffie-Hellman scheme is implemented with chaotic systems and ElGamal ...
IFIP Advances in Information and Communication Technology, 2015
ABSTRACT The price of copper and its variations represent a very important financial issue for mi... more ABSTRACT The price of copper and its variations represent a very important financial issue for mining companies and for the Chilean government because of its impact on the national economy. The price of commodities such as copper is highly volatile, dynamic and troublous. Due to this, forecasting is very complex. Using publicly data from October 24th of 2013 to August 29th of 2014 a multivaried based model using meta-heuristic optimization techniques is proposed. In particular, we use Genetic Algorithms and Simulated Annealing in order to find the best fitting parameters to forecast the variation on the copper price. A non-parametric test proposed by Timmermann and Pesaran is used to demonstrate the forecasting capacity of the models. Our numerical results show that the Genetic Algorithmic approach has a better performance than Simulated Annealing, being more effective for long range forecasting.
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