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Emotion learning: Solving a shortest path problem in an arbitrary deterministic environment in linear time with an emotional agent

Silvana P Etruseva (2008)

International Journal of Applied Mathematics and Computer Science

The paper presents an algorithm which solves the shortest path problem in an arbitrary deterministic environment with n states with an emotional agent in linear time. The algorithm originates from an algorithm which in exponential time solves the same problem, and the agent architecture used for solving the problem is an NN-CAA architecture (neural network crossbar adaptive array). By implementing emotion learning, the linear time algorithm is obtained and the agent architecture is modified. The...

Ensemble neural network approach for accurate load forecasting in a power system

Krzysztof Siwek, Stanisław Osowski, Ryszard Szupiluk (2009)

International Journal of Applied Mathematics and Computer Science

The paper presents an improved method for 1-24 hours load forecasting in the power system, integrating and combining different neural forecasting results by an ensemble system. We will integrate the results of partial predictions made by three solutions, out of which one relies on a multilayer perceptron and two others on self-organizing networks of the competitive type. As the expert system we will apply different integration methods: simple averaging, SVD based weighted averaging, principal component...

Enseñanza de la bioestadística en medicina.

M.ª Purificación Galindo Villardón (1996)

Qüestiió

Hasta hace tan sólo unos años, era característico en el profesional médico un profundo desconocimiento de la Metodología Estadística y su utilidad, un hecho claramente cuestionado. Gracias a la intensa labor divulgativa, la mayoría de los investigadores médicos reconocen ya la importancia de los Métodos Estadísticos. Contamos, al menos, con un notable cambio de actitud por parte de los investigadores médicos. Sin embargo, el papel adjuticado a la Estadística en los nuevos planes de estudio no está...

Epidemiology of Dengue Fever: A Model with Temporary Cross-Immunity and Possible Secondary Infection Shows Bifurcations and Chaotic Behaviour in Wide Parameter Regions

Maíra Aguiar, Bob Kooi, Nico Stollenwerk (2008)

Mathematical Modelling of Natural Phenomena

Basic models suitable to explain the epidemiology of dengue fever have previously shown the possibility of deterministically chaotic attractors, which might explain the observed fluctuations found in empiric outbreak data. However, the region of bifurcations and chaos require strong enhanced infectivity on secondary infection, motivated by experimental findings of antibody-dependent-enhancement. Including temporary cross-immunity in such models, which is common knowledge among field researchers...

Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays

Qianhong Zhang, Lihui Yang, Daixi Liao (2011)

International Journal of Applied Mathematics and Computer Science

Fuzzy cellular neural networks with time-varying delays are considered. Some sufficient conditions for the existence and exponential stability of periodic solutions are obtained by using the continuation theorem based on the coincidence degree and the differential inequality technique. The sufficient conditions are easy to use in pattern recognition and automatic control. Finally, an example is given to show the feasibility and effectiveness of our methods.

Currently displaying 101 – 120 of 297