Multi-objective optimization of TSK fuzzy models

Guenounou, Ouahib; Belmehdi, A.; Dahhou, B.

doi:10.1109/ssd.2008.4632782

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…There are five competing goals of the function in the reservoir group optimization dispatching MOP. We can use the fuzzy set theory to translate them into single-objective problem, using the descending half-line as their membership function [21,22], shown in Figure 4. The objective membership function can be described as follows:…”

Section: The Greatest Satisfaction Transformation Of the Reservoirmentioning

confidence: 99%

Multiobjective Optimization Problem of Multireservoir System in Semiarid Areas

Chen

Cheng

Yan

2013

Mathematical Problems in Engineering

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With the increasing scarcity of water resources, the growing importance of the optimization operation of the multireservoir system in water resources development, utilization, and management is increasingly evident. Some of the existing optimization methods are inadequate in applicability and effectiveness. Therefore, we need further research in how to enhance the applicability and effectiveness of the algorithm. On the basis of the research of the multireservoir system’s operating parameters in the Urumqi River basin, we establish a multiobjective optimization problem (MOP) model of water resources development, which meets the requirements of water resources development. In the mathematical model, the domestic water consumption is the biggest, the production of industry and agricultural is the largest, the gross output value of industry and agricultural is the highest, and the investment of the water development is the minimum. We use the weighted variable-step shuffled frog leaping algorithm (SFLA) to resolve it, which satisfies the constraints. Through establishing the test function and performance metrics, we deduce the evolutionary algorithms, which suit for solving MOP of the scheduling, and realize the multiobjective optimization of the multireservoir system. After that, using the fuzzy theory, we convert the competitive multiobjective function into single objective problem of maximum satisfaction, which is the only solution. A feasible solution is provided to resolve the multiobjective scheduling optimization of multireservoir system in the Urumqi River basin. It is the significance of the layout of production, the regional protection of ecological environment, and the sufficient and rational use of natural resources, in Urumqi and the surrounding areas.

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Section: The Greatest Satisfaction Transformation Of the Reservoirmentioning

confidence: 99%

Multiobjective Optimization Problem of Multireservoir System in Semiarid Areas

Chen

Cheng

Yan

2013

Mathematical Problems in Engineering

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“…With the robustness and the search ability, EAs such genetic algorithms (GAs), evolutionary strategy (ES), and particle swarm optimizer (PSO) have been applied in fuzzy modeling (Guenounou, Belmehdi, & Dahhou, 2009;Kang, Woo, Hwang, & Woo, 2000;Roubos & Setnes, 2001;Setnes & Roubos, 2000;Yen, Wang, & Gillespie, 1998;Zhao, Yang, & Zeng, 2009). In some methods (Guenounou et al, 2009;Roubos & Setnes, 2001;Setnes & Roubos, 2000), the identification of the T-S model can be divided into two step: first clustering techniques are applied to obtain an initial model; then EAs are applied to adjust the parameters of the model. That is to say that the structural optimization is carried out independently from parameter optimization.…”

Section: Introductionmentioning

confidence: 99%

Differential evolution and quantum-inquired differential evolution for evolving Takagi–Sugeno fuzzy models

Su¹,

Yang²

2011

Expert Systems with Applications

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“…Mejorando la interpretabilidad del modelado difuso preciso, sin disminuir su grado de exactitud [31]. Una forma de obtener dicha mejora es reduciendo la complejidad de los modelos [47,64,[79][80][81][82][83][84][85][86][87][88][89]. 3.…”

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Análisis del equilibrio entre precisión e interpretabilidad de los sistemas basados en reglas difusas lingüísticos y aproximativos

Hernández¹

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Capítulo 1. Introducción medades [7][8][9], mercadotecnia [10,11], conducta humana [12,13], modelos sobre consumo [14,15], ... Los modelos capturan una percepción imperfecta de la realidad, son una versión simplificada de la realidad. Estos modelos pueden tener distintas funciones: Explicar Fenómenos como ocurre con la mayor parte de las teorías del campo de la Física, Hacer Predicciones sobre el desarrollo futuro de aspectos del mundo real, Toma de Decisiones y Comunicación del conocimiento.Los conceptos involucrados en el desarrollo de modelos en elámbito técnicocientífico se resumen en: variables, relaciones y datos. Hoy en día un aspecto básico de todos estos modelos es su formulación que debe ser adecuada para su implementación mediante sistemas de computación.De acuerdo a [16], los modelos pueden llevar a cabo dos funciones representativas diferentes. Por un lado pueden representar un aspecto del mundo real, distinguiéndose entonces dos tipos de modelos distintos en función de la naturaleza del objetivo: modelos de los fenómenos o modelos de datos. Y por otro lado, un modelo también puede representar una teoría. Desde el punto de vista del trabajo realizado en esta tesis, los modelos de datos serán el eje central de la misma.Un modelo de datos es "una versión corregida, rectificada, reglamentada, y en muchos casos idealizada de los datos que obtenemos de la observación inmediata, los llamados datos en bruto" [16]. Los modelos de datos tienen un papel esencial en la confirmación de teorías, porque es el modelo de datos y no los datos en bruto lo que se compara con una predicción teórica. La generación de estos modelos puede ser extremadamente compleja, requiriendo avanzadas técnicas y metodologías exhaustivas para alcanzar el objetivo de una manera eficiente.En esta tesis partiremos de estas ideas claves: modelos, datos, computación y

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Multi-objective optimization of TSK fuzzy models

Abstract: O~if i == nl + 1, , nl + n2 u; == OJ if i == nl + .. + nj-l + 1, , nl + .. + nj (4)

Cited by 3 publications

References 14 publications

Multiobjective Optimization Problem of Multireservoir System in Semiarid Areas

Multiobjective Optimization Problem of Multireservoir System in Semiarid Areas

Differential evolution and quantum-inquired differential evolution for evolving Takagi–Sugeno fuzzy models

Análisis del equilibrio entre precisión e interpretabilidad de los sistemas basados en reglas difusas lingüísticos y aproximativos

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