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120,194
Genetic Algorithm Optimization of Superresolution Parameters
"... Superresolution is the process of producing a high resolution image from a collection of low resolution images. This process has potential application in a wide spectrum of fields in which navigation, surveillance, and observation are important, yet in which target images have limited resolution. Th ..."
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Cited by 2 (0 self)
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) parameters for superresolution is proposed and implemented, and a superresolved image is generated using genetic algorithm optimization of an existing superresolution method.
Technology. Accessed from Genetic Algorithm Optimization Applied to Planar and Wire Antennas
, 2007
"... Genetic algorithm optimization applied to planar and wire antennas ..."
Genetic Algorithm Optimization of Space Frame
"... Structural design of space frames requires appropriate form for a structure so that it can carry the imposed loads safely and economically. Traditional approaches towards the task of finding such forms for structures have been by the use of experimental models or by intuition and experience. The mai ..."
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programs are not designed as optimization tools. In this study for optimization of multistory structures, home written MATLAB code interface program is designed to connect SAP2000 which is known as a commercial nonlinear finite element program and genetic algorithm optimization program. The design
Lithographically-definable Solar Cell Random Reflector using Genetic Algorithm Optimization
, 2016
"... Lithographically-definable solar cell random reflector using genetic algorithm optimization ..."
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Cited by 1 (1 self)
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Lithographically-definable solar cell random reflector using genetic algorithm optimization
Genetic Algorithm Optimization for Mooring Systems
"... Abstract The present article describes the application of Genetic Algorithms (GA) [1] to mooring systems used in offshore oil exploitation. The GA seeks an optimum positioning of the anchors that minimizes the vessel offset due to environmental conditions such as wind, wave and sea currents. The com ..."
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Abstract The present article describes the application of Genetic Algorithms (GA) [1] to mooring systems used in offshore oil exploitation. The GA seeks an optimum positioning of the anchors that minimizes the vessel offset due to environmental conditions such as wind, wave and sea currents
An Adaptive Penalty Approach for Constrained Genetic-Algorithm Optimization
- Proceedings of the Third Annual Genetic Programming Conference
, 1998
"... In this paper we describe a new adaptive penalty approach for handling constraints in genetic algorithm optimization problems. The idea is to start with a relatively small penalty coefficient and then increase it or decrease it on demand as the optimization progresses. Empirical results in several e ..."
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Cited by 9 (2 self)
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In this paper we describe a new adaptive penalty approach for handling constraints in genetic algorithm optimization problems. The idea is to start with a relatively small penalty coefficient and then increase it or decrease it on demand as the optimization progresses. Empirical results in several
Genetic Algorithm Optimization of Fractal-Random Arrays
"... Abstract – The two most commonly used antenna array layouts, the periodic array and the random array, have beneficial properties which are mutually exclusive of each other. In order to combine the positive properties of both types of arrays into one design successfully, researchers are focusing on a ..."
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on a class of arrays that has both periodic and random structures: fractal-random arrays. In addition, researchers have used genetic algorithms, global optimization computer models based on natural selection, to find successful solutions for layout problems. This paper introduces a type of nature
Genetic Algorithms for Multiobjective Optimization: Formulation, Discussion and Generalization
, 1993
"... The paper describes a rank-based fitness assignment method for Multiple Objective Genetic Algorithms (MOGAs). Conventional niche formation methods are extended to this class of multimodal problems and theory for setting the niche size is presented. The fitness assignment method is then modified to a ..."
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Cited by 633 (15 self)
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to allow direct intervention of an external decision maker (DM). Finally, the MOGA is generalised further: the genetic algorithm is seen as the optimizing element of a multiobjective optimization loop, which also comprises the DM. It is the interaction between the two that leads to the determination of a
Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms
- Evolutionary Computation
, 1994
"... In trying to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly sensitive to the weight vector used in the scalarization process and demands the user to have knowledge about t ..."
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Cited by 539 (5 self)
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the underlying problem. Moreover, in solving multiobjective problems, designers may be interested in a set of Pareto-optimal points, instead of a single point. Since genetic algorithms(GAs) work with a population of points, it seems natural to use GAs in multiobjective optimization problems to capture a
Genetic algorithm optimization for a surgical ultrasonic transducer
- In Ultrasonics Symposium, 2008. IUS 2008. IEEE
, 2008
"... Abstract-An ultrasonic piezoelectric transducer to cut the human tissue or to remove the spinal disc is envisioned to improve efficiency and facilitate the surgeons work. Three genetic algorithms have been developed. The first one is based on conditional genetic operators, the second one is based o ..."
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Cited by 1 (0 self)
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Abstract-An ultrasonic piezoelectric transducer to cut the human tissue or to remove the spinal disc is envisioned to improve efficiency and facilitate the surgeons work. Three genetic algorithms have been developed. The first one is based on conditional genetic operators, the second one is based
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