6 research outputs found

    Artificial analysis of molecular marker loci linked to tree resistance response by an artificial neural network

    Get PDF
    One of the biggest challenges that software developers face is to make an accurate estimate of the project effort. Radial basis function neural networks have been used to software effort estimation in this work using NASA dataset. This paper evaluates and compares radial basis function versus a regression model. The results show that radial basis function neural network have obtained less Mean Square Error than the regression method

    Uniform Distributed Pushdown Automata Systems.

    Get PDF
    We consider here uniform distributed pushdown automata systems (UDPAS), namely distributed pushdown automata systems having all components identical pushdown automata. We consider here just a single protocol for activating/deactivating components, namely a component stays active as long as it can perform moves, as well as two ways of accepting the input word: by empty stacks (all components have empty stacks) or by final states (all components are in final states), when the input word is completely read. We mainly investigate the computational power of UDPAS accepting by empty stacks and a few decidability and closure properties of the families of languages they define. Some directions for further work and open problems are also discussed

    Prion crystalization model and its application to recognition pattern

    Get PDF
    This paper introduces APA (?Artificial Prion Assembly?): a pattern recognition system based on artificial prion crystalization. Specifically, the system exhibits the capability to classify patterns according to the resulting prion self- assembly simulated with cellular automata. Our approach is inspired in the biological process of proteins aggregation, known as prions, which are assembled as amyloid fibers related with neurodegenerative disorders

    Suitability of artificial neural networks for designing LoC circuits

    Get PDF
    he simulation of complex LoC (Lab-on-a-Chip) devices is a process that requires solving computationally expensive partial differential equations. An interesting alternative uses artificial neural networks for creating computationally feasible models based on MOR techniques. This paper proposes an approach that uses artificial neural networks for designing LoC components considering the artificial neural network topology as an isomorphism of the LoC device topology. The parameters of the trained neural networks are based on equations for modeling microfluidic circuits, analogous to electronic circuits. The neural networks have been trained to behave like AND, OR, Inverter gates. The parameters of the trained neural networks represent the features of LoC devices that behave as the aforementioned gates. This would mean that LoC devices universally compute

    Modeling, simulation and application of bacterial transduction in genetic algorithms

    Get PDF
    At present, all methods in Evolutionary Computation are bioinspired by the fundamental principles of neo-Darwinism, as well as by a vertical gene transfer. Virus transduction is one of the key mechanisms of horizontal gene propagation in microorganisms (e.g. bacteria). In the present paper, we model and simulate a transduction operator, exploring the possible role and usefulness of transduction in a genetic algorithm. The genetic algorithm including transduction has been named PETRI (abbreviation of Promoting Evolution Through Reiterated Infection). Our results showed how PETRI approaches higher fitness values as transduction probability comes close to 100%. The conclusion is that transduction improves the performance of a genetic algorithm, assuming a population divided among several sub-populations or ?bacterial colonies?

    Una formalizaciĂłn de las relaciones entre distintas representaciones del conocimiento

    Full text link
    La presente tesis desarrolla a partir de los conceptos de marcos y reglas produccion una estructuracion de estos dos formalismos de representacion del conocimiento.se comprueba que los marcos y las reglas con sus operaciones asociadas tienen una estructura algebraica de espacio vectorial. Para ello se dota al conjunto de marcos de una operacion interna demostrandose que con ella se tiene estructura de grupo abeliano. Se definen dos operaciones en el conjunto de las reglas basandose en las conjunciones y disyunciones logicas cumplienose que las reglas con estas operaciones definidas es cu cuerpo. Por ultimo se define una operacion externa del conjunto de reglas por el conjunto de marcos en el conjunto de marcos verificando las propiedades de espacio vectorial uno de los resultados pragmaticos de esta tesis es el poder establecer un nucleo comun de desarrollo de sistemas expertos en areas tan dispersas como son las finanzas la administracion publica o la educacion
    corecore