En este artículo mostraremos la conveniencia de emplear aprendizaje mediante enlace genético como... more En este artículo mostraremos la conveniencia de emplear aprendizaje mediante enlace genético como alternativa en mejorar los recorridos y trayectorias de búsquedas de los cromosomas. Mostraremos las distintas formas de representación que se han estudiado, haciendo un énfasis en los mecanismos de evolución de los mismos.
La presente investigación, se ubica en el área de la Inteligencia Artificial conocida como selecc... more La presente investigación, se ubica en el área de la Inteligencia Artificial conocida como selección de características (SSC) en aprendizaje no supervisado (ANS) haciendo uso de un algoritmo genético, modificado con un nuevo operador especial para el problema de selección de subconjuntos de características denominado "operador genético de aceleración". Este operador reduce los tiempos desde horas o días a minutos. La metodología diseñada, realiza selección de características de forma que se conserva la representatividad del conjunto de datos original, pero reduciendo el tamaño de éste, facilitando su manejo y minimizando los costos de manipulación. Ésto, para encontrar agrupaciones tanto de casos como de variables utilizando el peso informacional de las mismas. Las principales aportaciones de la metodología reportada, son el operador de aceleración, el mecanismo de mejoramiento en el proceso de búsqueda de testores típicos en una Matriz Básica obtenida a partir de una base...
This paper presents a set of evolutionary mechanisms embedded on an estimation of distribution al... more This paper presents a set of evolutionary mechanisms embedded on an estimation of distribution algorithm (MITEDA-AC) that performs the synthesis of an analog low pass filter. Analog circuits are modeled with linked lists in order to represent and evolve both, topology and sizing. The developed representation mechanism ensures that generated circuits be feasible, and in order to reduce the gap between real circuits and those evolvable, the concept of preferred values was included on representation and generation mechanisms. The algorithm interacts with SPICE to performance evaluation of each individual in the population. MITEDA-AC was inspired by the COMIT because like this, it uses bivariate probability distributions to generate the optimal dependency tree, but without local optimizers. Features integrated in the learning mechanism of this evolvable algorithm, were the number of capacitors, resistors and inductors included in each circuit of the population. This paper describes the ...
Evolutionary computation algorithms are stochastic optimization methods; they are conveniently pr... more Evolutionary computation algorithms are stochastic optimization methods; they are conveniently presented using the metaphor of natural evolution: a randomly initialized population of individuals evolves following a simulation of the Darwinian principle. New individuals are generated using genetic operations such as mutation and crossover. The probability of survival of the newly generated solutions depends on their fitness (Michalewicz et al., 1995). Evolutionary algorithms (EAs) have been successfully used to solve different types of optimization problems (Back, 1996). In the most general terms, evolution can be described as a two-step iterative process, consisting of random variation followed by selection. The structure of any evolutionary computation algorithm is shown in the figure 1.
El diagnóstico oportuno forma parte de una serie de recomendaciones que permiten detectar enferme... more El diagnóstico oportuno forma parte de una serie de recomendaciones que permiten detectar enfermedades en etapas tempranas y puedan ser atacadas antes de que conduzcan a problemas serios o incluso la muerte. Debido a su importancia, el diagnóstico médico es un proceso cognoscitivo que debe mantenerse en constante evolución con el objetivo de reducir la posibilidad de un diagnóstico erróneo. En casos de cáncer, el diagnóstico oportuno es determinante para conseguir un pronóstico positivo. Por tanto, se presenta un análisis sobre las características de las células de cáncer, específicamente en cáncer de mama. Dicha patología es de los tipos de cáncer más presente en mujeres alrededor del mundo sin importar el nivel de desarrollo de la región. El propósito del artículo es presentar el uso de testores típicos, es decir, como técnica de reducción de dimensiones para clasificar las células cancerígenas en malignas o benignas; así como el peso informacional de cada variable como índice de ...
Actualmente la Inteligencia Artificial es un area de la ciencia de gran interes por ser un area m... more Actualmente la Inteligencia Artificial es un area de la ciencia de gran interes por ser un area multidiciplinaria donde se realizan sistemas que tratan de hacer tareas y resolver problemas como lo hace un humano, asi mismo se trata de simular de manera artificial las formas del pensamiento y como trabaja el cerebro para tomar desiciones. Aunque en la realidad aun no se a podido realizar todo lo que las personas sueñan al conocer esta area o al ver lo que se muestra en la ciencia ficcion es un area que poco a poco va ganando terreno al estar presente en muchas aplicaciones, aparatos, dispositivos que utilizamos de manera cotidiana.
Logistics Management and Optimization through Hybrid Artificial Intelligence Systems, 2012
This chapter presents the implementation of a Genetic Algorithm into a framework for machine lear... more This chapter presents the implementation of a Genetic Algorithm into a framework for machine learning that deals with the problem of identifying the factors that impact the health state of newborns in Mexico. Experimental results show a percentage of correct clustering for unsupervised learning of 89%, a real life training matrix of 46 variables, was reduced to only 25 that represent 54% of its original size. Moreover execution time is about one and a half minutes. Each risk factor (of neonatal health) found by the algorithm was validated by medical experts. The contribution to the medical field is invaluable, since the cost of monitoring these features is minimal and it can reduce neonatal mortality in our country.
... CP 20100. México {mdtorres,eponce,atorres}@correo.uaa.mx, elva.diaz@itesm.mx 2 Universidad Au... more ... CP 20100. México {mdtorres,eponce,atorres}@correo.uaa.mx, elva.diaz@itesm.mx 2 Universidad Autónoma de Ciudad Juárez, Instituto de Ingeniería y Tecnología, Departamento de Ingeniería Eléctrica y Computación. ... End /* Hybridized Evolutionary AG for FSS in Learning* ...
ABSTRACT This paper presents a hybrid evolutionary algorithm to identify risk factors associated ... more ABSTRACT This paper presents a hybrid evolutionary algorithm to identify risk factors associated with transfusion related acute lung injury (TRALI). This medical condition occurs mainly in intensive care units and operating rooms, and the main strategy for its treatment is prevention. The proposed algorithm works with information from the model known as "two hits", in which the first hit is the original disease and the second corresponds to the blood transfusion. This algorithm is based on a genetic algorithm hybridized with testor analysis. This research used information from 87 patients treated at the Centenary Hospital Miguel Hidalgo in the city of Aguascalientes, Mexico. As a result of the algorithm's application, it was found that most variables are related to the first hit, while only some of them belong to the second one. The analysis also revealed that some variables physicians believed significant a priori, were not very important; among other discoveries.
ABSTRACT This paper presents a hybrid evolutionary algorithm to identify risk factors associated ... more ABSTRACT This paper presents a hybrid evolutionary algorithm to identify risk factors associated with transfusion related acute lung injury (TRALI). This medical condition occurs mainly in intensive care units and operating rooms, and the main strategy for its treatment is prevention. The proposed algorithm works with information from the model known as "two hits", in which the first hit is the original disease and the second corresponds to the blood transfusion. This algorithm is based on a genetic algorithm hybridized with testor analysis. This research used information from 87 patients treated at the Centenary Hospital Miguel Hidalgo in the city of Aguascalientes, Mexico. As a result of the algorithm's application, it was found that most variables are related to the first hit, while only some of them belong to the second one. The analysis also revealed that some variables physicians believed significant a priori, were not very important; among other discoveries.
... CP 20100. México {mdtorres,eponce,atorres}@correo.uaa.mx, elva.diaz@itesm.mx 2 Universidad Au... more ... CP 20100. México {mdtorres,eponce,atorres}@correo.uaa.mx, elva.diaz@itesm.mx 2 Universidad Autónoma de Ciudad Juárez, Instituto de Ingeniería y Tecnología, Departamento de Ingeniería Eléctrica y Computación. ... End /* Hybridized Evolutionary AG for FSS in Learning* ...
En este artículo mostraremos la conveniencia de emplear aprendizaje mediante enlace genético como... more En este artículo mostraremos la conveniencia de emplear aprendizaje mediante enlace genético como alternativa en mejorar los recorridos y trayectorias de búsquedas de los cromosomas. Mostraremos las distintas formas de representación que se han estudiado, haciendo un énfasis en los mecanismos de evolución de los mismos.
La presente investigación, se ubica en el área de la Inteligencia Artificial conocida como selecc... more La presente investigación, se ubica en el área de la Inteligencia Artificial conocida como selección de características (SSC) en aprendizaje no supervisado (ANS) haciendo uso de un algoritmo genético, modificado con un nuevo operador especial para el problema de selección de subconjuntos de características denominado "operador genético de aceleración". Este operador reduce los tiempos desde horas o días a minutos. La metodología diseñada, realiza selección de características de forma que se conserva la representatividad del conjunto de datos original, pero reduciendo el tamaño de éste, facilitando su manejo y minimizando los costos de manipulación. Ésto, para encontrar agrupaciones tanto de casos como de variables utilizando el peso informacional de las mismas. Las principales aportaciones de la metodología reportada, son el operador de aceleración, el mecanismo de mejoramiento en el proceso de búsqueda de testores típicos en una Matriz Básica obtenida a partir de una base...
This paper presents a set of evolutionary mechanisms embedded on an estimation of distribution al... more This paper presents a set of evolutionary mechanisms embedded on an estimation of distribution algorithm (MITEDA-AC) that performs the synthesis of an analog low pass filter. Analog circuits are modeled with linked lists in order to represent and evolve both, topology and sizing. The developed representation mechanism ensures that generated circuits be feasible, and in order to reduce the gap between real circuits and those evolvable, the concept of preferred values was included on representation and generation mechanisms. The algorithm interacts with SPICE to performance evaluation of each individual in the population. MITEDA-AC was inspired by the COMIT because like this, it uses bivariate probability distributions to generate the optimal dependency tree, but without local optimizers. Features integrated in the learning mechanism of this evolvable algorithm, were the number of capacitors, resistors and inductors included in each circuit of the population. This paper describes the ...
Evolutionary computation algorithms are stochastic optimization methods; they are conveniently pr... more Evolutionary computation algorithms are stochastic optimization methods; they are conveniently presented using the metaphor of natural evolution: a randomly initialized population of individuals evolves following a simulation of the Darwinian principle. New individuals are generated using genetic operations such as mutation and crossover. The probability of survival of the newly generated solutions depends on their fitness (Michalewicz et al., 1995). Evolutionary algorithms (EAs) have been successfully used to solve different types of optimization problems (Back, 1996). In the most general terms, evolution can be described as a two-step iterative process, consisting of random variation followed by selection. The structure of any evolutionary computation algorithm is shown in the figure 1.
El diagnóstico oportuno forma parte de una serie de recomendaciones que permiten detectar enferme... more El diagnóstico oportuno forma parte de una serie de recomendaciones que permiten detectar enfermedades en etapas tempranas y puedan ser atacadas antes de que conduzcan a problemas serios o incluso la muerte. Debido a su importancia, el diagnóstico médico es un proceso cognoscitivo que debe mantenerse en constante evolución con el objetivo de reducir la posibilidad de un diagnóstico erróneo. En casos de cáncer, el diagnóstico oportuno es determinante para conseguir un pronóstico positivo. Por tanto, se presenta un análisis sobre las características de las células de cáncer, específicamente en cáncer de mama. Dicha patología es de los tipos de cáncer más presente en mujeres alrededor del mundo sin importar el nivel de desarrollo de la región. El propósito del artículo es presentar el uso de testores típicos, es decir, como técnica de reducción de dimensiones para clasificar las células cancerígenas en malignas o benignas; así como el peso informacional de cada variable como índice de ...
Actualmente la Inteligencia Artificial es un area de la ciencia de gran interes por ser un area m... more Actualmente la Inteligencia Artificial es un area de la ciencia de gran interes por ser un area multidiciplinaria donde se realizan sistemas que tratan de hacer tareas y resolver problemas como lo hace un humano, asi mismo se trata de simular de manera artificial las formas del pensamiento y como trabaja el cerebro para tomar desiciones. Aunque en la realidad aun no se a podido realizar todo lo que las personas sueñan al conocer esta area o al ver lo que se muestra en la ciencia ficcion es un area que poco a poco va ganando terreno al estar presente en muchas aplicaciones, aparatos, dispositivos que utilizamos de manera cotidiana.
Logistics Management and Optimization through Hybrid Artificial Intelligence Systems, 2012
This chapter presents the implementation of a Genetic Algorithm into a framework for machine lear... more This chapter presents the implementation of a Genetic Algorithm into a framework for machine learning that deals with the problem of identifying the factors that impact the health state of newborns in Mexico. Experimental results show a percentage of correct clustering for unsupervised learning of 89%, a real life training matrix of 46 variables, was reduced to only 25 that represent 54% of its original size. Moreover execution time is about one and a half minutes. Each risk factor (of neonatal health) found by the algorithm was validated by medical experts. The contribution to the medical field is invaluable, since the cost of monitoring these features is minimal and it can reduce neonatal mortality in our country.
... CP 20100. México {mdtorres,eponce,atorres}@correo.uaa.mx, elva.diaz@itesm.mx 2 Universidad Au... more ... CP 20100. México {mdtorres,eponce,atorres}@correo.uaa.mx, elva.diaz@itesm.mx 2 Universidad Autónoma de Ciudad Juárez, Instituto de Ingeniería y Tecnología, Departamento de Ingeniería Eléctrica y Computación. ... End /* Hybridized Evolutionary AG for FSS in Learning* ...
ABSTRACT This paper presents a hybrid evolutionary algorithm to identify risk factors associated ... more ABSTRACT This paper presents a hybrid evolutionary algorithm to identify risk factors associated with transfusion related acute lung injury (TRALI). This medical condition occurs mainly in intensive care units and operating rooms, and the main strategy for its treatment is prevention. The proposed algorithm works with information from the model known as "two hits", in which the first hit is the original disease and the second corresponds to the blood transfusion. This algorithm is based on a genetic algorithm hybridized with testor analysis. This research used information from 87 patients treated at the Centenary Hospital Miguel Hidalgo in the city of Aguascalientes, Mexico. As a result of the algorithm's application, it was found that most variables are related to the first hit, while only some of them belong to the second one. The analysis also revealed that some variables physicians believed significant a priori, were not very important; among other discoveries.
ABSTRACT This paper presents a hybrid evolutionary algorithm to identify risk factors associated ... more ABSTRACT This paper presents a hybrid evolutionary algorithm to identify risk factors associated with transfusion related acute lung injury (TRALI). This medical condition occurs mainly in intensive care units and operating rooms, and the main strategy for its treatment is prevention. The proposed algorithm works with information from the model known as "two hits", in which the first hit is the original disease and the second corresponds to the blood transfusion. This algorithm is based on a genetic algorithm hybridized with testor analysis. This research used information from 87 patients treated at the Centenary Hospital Miguel Hidalgo in the city of Aguascalientes, Mexico. As a result of the algorithm's application, it was found that most variables are related to the first hit, while only some of them belong to the second one. The analysis also revealed that some variables physicians believed significant a priori, were not very important; among other discoveries.
... CP 20100. México {mdtorres,eponce,atorres}@correo.uaa.mx, elva.diaz@itesm.mx 2 Universidad Au... more ... CP 20100. México {mdtorres,eponce,atorres}@correo.uaa.mx, elva.diaz@itesm.mx 2 Universidad Autónoma de Ciudad Juárez, Instituto de Ingeniería y Tecnología, Departamento de Ingeniería Eléctrica y Computación. ... End /* Hybridized Evolutionary AG for FSS in Learning* ...
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