Particle Swarm
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Aplicación del Algoritmo Particle Swarm Optimization al Problema de Optimización de Colocación de Convertidores de Longitud de Onda en Redes WRON con Diferentes Tipos de Enrutamiento Edición Única
... el particle swarm optimization (PSO), un algoritmo de búsqueda para resolver problemas de optimización, aplicado a la resolución del wavelength converters placement ...
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Estimation of the particle size distribution of colloids from multiangle dynamic light scattering measurements with particle swarm optimization
... and swarm intelligent algorithm (Bermeo et ...a particle swarm optimization (PSO), and the PSD was assumed to be represented only by an exponentially modified Gaussian (EMG) ...
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Polynomial approximation using particle swarm optimization of lineal enhanced neural networks with no hidden layers.
... Obviously, a neural network with i input neurons, h hidden neurons and o output neurons it has (i+1)h +(h +1)o weights and therefore, individuals of the PSO have (i + 1)h + (h + 1)o dimensions. By considering such ...
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A particle swarm optimizer for multi-objective optimization
... the particle swarm is initialized with random values corresponding to the ranges of the decision variables, these values are dependent on the test ...the swarm is evaluated using the corresponding ...
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Particle swarm optimization aplicado a la programación de los ciclos de semáforos en Bahía Blanca
... En este trabajo presentamos un algoritmo PSO (Particle Swarm Optimiza- tion) [11] como optimizador de programas de ciclos de sem´aforos. Para la evalu- aci´on de los programas de ciclos generados ...
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Global numerical optimization with a bi-population particle swarm optimizer
... This paper presents an enhanced Particle Swarm Optimizer approach, which is designed to solve numerical unconstrained optimization problems. The approach incorporates a dual population in an attempt to ...
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CALIBRATION OF SEMI ANALYTIC MODELS OF GALAXY FORMATION USING PARTICLE SWARM OPTIMIZATION
... called Particle Swarm Optimization ( PSO ) , a self-learning algorithm for localizing regions of maximum likelihood in multidimensional spaces that outperforms traditional sampling methods in terms of ...
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Particle Swarm Optimization and Uncertainty Assessment in Inverse Problems
... Abstract: Most inverse problems in the industry (and particularly in geophysical exploration) are highly underdetermined because the number of model parameters too high to achieve accurate data predictions and because ...
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Multicast routing and wavelength assignment in optical networks with particle swarm optimization
... Abstract. Large bandwidth on hand in WDM networks is the best choice for increasing traffic demand; although, routing and wavelength assignment (RWA) problems still remain a challenge. This work proposes a novel method ...
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PARTICLE SWARM OPTIMIZATION PARA EL AJUSTE DE MODELOS PROBABILISTICOS A DATOS DEL VIENTO EN VALPARAÍSO
... meta-heur´ıstica Particle Swarm Optimization ha demostrado conseguir buenos resultados, en diversos conjuntos de datos provenientes de distintas zonas del ...
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An´alisis de medidas no-supervisadas de calidad en clusters obtenidos por K-means y Particle Swarm Optimization
... denominada Particle Swarm Optimization (PSO) y un algoritmo h´ıbrido, que combina las caracter´ısticas de los dos algoritmos anteriores, denominado ...
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A particle swarm optimizer for multi-objective optimization
... the particle swarm is initialized with random values corresponding to the ranges of the decision variables, these values are dependent on the test ...the swarm is evaluated using the corresponding ...
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Automatic placement of electronic components to maximize heat dissipation on PCB's using particle swarm optimization
... This thesis documents my personal research as candidate for the academic degree of Master of Science in Intelligent Systems. The purpose of this work is to optimize the electronic components layout in a printed circuit ...
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Particle swarm optimization para un problema de optimización combinatoria
... El algoritmo propuesto es validado usando instancias tomadas de la OR-Library y los resultados son comparados con los obtenidos por un algoritmo evolutivo multirecombinado que incluye conocimiento acerca del problema y ...
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The Optimal combination: Grammatical Swarm, Particle Swarm Optimization and Neural Networks.
... the particle swarm make the technique resilient to the problem of local minima ...Grammatical swarm (GS) adopts a particle swarm learning algorithm which is linked to a grammatical ...
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Particle swarm optimization para problemas de secuenciamiento: total weighted tardiness
... Particle Swarm Optimization (PSO) ha sido utilizado exitosamente en diferentes áreas como optimización mutidimensional y multiobjetivo, y entrenamiento de redes neuronales entre otras, pero existen ...
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Differential Evoluiton - Particle Swarm Optimization
... new particle should be created according to formulas (d) for the velocity and (e) for the new ...created particle is proven to be better, it should be replaced by the old one for the next ...best ...
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Una comparativa del algoritmo particle swarm optimization con restricciones entre los métodos de factor de constricción y neighborhood con coeficiente bde inercia dinámico
... algoritmo Particle Swarm Optimization (PSO) fue propuesto por Kennedy y Eberhart [1] inspirado en la simulación del comportamiento social de bandada de ...
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Propuesta de Mejora de la Programación de la Producción Basada en Métodos Cuantitativos en la Empresa Café Semilla S A S en Bogotá D C
... [10]. Swarm particle optimization was developed initially by Kennedy, Eberhart [11] and sequences are individuals of a swarm, each one with a value of the objective ...the swarm with the best ...
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Metaheurísticas poblacionales aplicadas a la resolución de problemas complejos
... Esta línea de trabajo está basada en la investigación y aplicación de metaheurísticas poblacionales para la resolución de problemas multi-objetivo. En particular, se selecciona la metaheurística conocida como ...
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