نتایج جستجو برای: Multi-objective genetic algorithm (MOGA)

تعداد نتایج: 2159089  

Journal: :journal of medical signals and sensors 0
toktam khatibi mohammad mehdi sepehri pejman shadpour

background: laparoscopy or minimally invasive surgery is a surgical procedure in which laparoscope and other surgical instruments are inserted inside body via a few small incisions. laparoscope is used to look inside the patient's body and records displayed images. temporal segmentation of laparoscopic videos has many applications like detecting laparoscopic anomalies and interrupts. it is prer...

Journal: :iranian journal of fuzzy systems 2012
mojtaba eftekhari mahdi eftekhari maryam majidi hossein nezamabadi pour

in this study, a multi-objective genetic algorithm (moga) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear multi-input multi-output (mimo) systems. in the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. furthermore, se- curing low-level and high-level ...

In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level ...

2002
Nattavut Keerativuttitumrong Nachol Chaiyaratana Vara Varavithya

This paper presents the integration between two types of genetic algorithm: a multi-objective genetic algorithm (MOGA) and a co-operative co-evolutionary genetic algorithm (CCGA). The resulting algorithm is referred to as a multi-objective co-operative co-evolutionary genetic algorithm or MOCCGA. The integration between the two algorithms is carried out in order to improve the performance of th...

2001
Tadahiko Murata Hisao Ishibuchi Mitsuo Gen

When we try to implement a multi-objective genetic algorithm (MOGA) with variable weights for finding a set of Pareto optimal solutions, one difficulty lies in determining appropriate search directions for genetic search. In our MOGA, a weight value for each objective in a scalar fitness function was randomly specified. Based on the fitness function with the randomly specified weight values, a ...

Journal: :Transactions of the Japanese Society for Artificial Intelligence 2009

2006
M. JANGA NAGESH KUMAR

This paper presents a Multi-objective Evolutionary Algorithm (MOEA) to derive a set of optimal operation policies for a multipurpose reservoir system. One of the main goals in multiobjective optimization is to find a set of well distributed optimal solutions along the Pareto front. Classical optimization methods often fail in attaining a good Pareto front. To overcome the drawbacks faced by the...

2015
Zou Yingyong Li Qinghua

Based on the analysis on the basic principles and characteristics of the existing multiobjective genetic algorithm (MOGA), an improved multi-objective GA with elites maintain is put forward based on non-dominated sorting genetic algorithm (NSGA). NSGA-II algorithm theory and parallel hybrid evolutionary theory is described in detail. The design principle, process and detailed implementations of...

2014
Tomohiro Yoshikawa Toru Yoshida

Recently, a lot of studies on Multi-Objective Genetic Algorithm (MOGA), in which Genetic Algorithm is applied to Multi-objective Optimization Problems (MOPs), have been reported actively. MOGA has been also applied to engineering design fields, then it is important not only to obtain Pareto solutions having high performance but also to analyze the obtained Pareto solutions and extract the knowl...

2012
M. EFTEKHARI M. MAJIDI

In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of nonlinear system identification, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, securing low-level and high-level int...

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