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61
Control of nonlinear dynamical systems using genetic algorithms
Published 1997“…This paper introduces a new method for the control of nonlinear systems using genetic algorithms. The proposed method formulates the nonlinear controller design as an optimization problem and genetic algorithms are used in the optimization process. …”
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62
Capturing outline of fonts using genetic algorithm and splines
Published 2001“…We present a method to convert the original problem into a discrete combinatorial optimization problem and solve it by a genetic algorithm. …”
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63
Timing driven genetic algorithm for standard-cell placement
Published 1995“…As the algorithm starts converging toward generations with acceptable delay properties, the objective is dynamically adjusted toward optimizing area and routability. …”
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64
A new genetic algorithm approach for unit commitment
Published 1997“…This paper presents a new genetic algorithm approach to solve the unit commitment problem in electric power systems. …”
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65
A method for test scheduling using an evolutionary approach. (c2000)
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masterThesis -
66
Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
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doctoralThesis -
67
Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms
Published 2007“…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …”
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68
Genetic Algorithm Based Simultaneous Eigenvalue Placement Of Power Systems
Published 2020“…The task of selecting the output feedback gains is converted to a simple optimization problem with an eigenvaluebased objective function, which is solved by a genetic algorithm. …”
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69
Graph contraction for physical optimization methods
Published 1993“…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, Genetic Algorithm and Simulated Annealing. …”
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conferenceObject -
70
Performance Assessment of Foraging Algorithms vs. Evolutionary Algorithms
Published 2012“…This work provides a complete performance assessment of the four mentioned algorithms in comparison to the widely known differential evolution (DE), genetic algorithms (GAs), harmony search (HS), and particle swarm optimization (PSO) algorithms when applied to the problem of unconstrained nonlinear continuous function optimization. …”
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71
Genetic algorithm assisted support vector machine for M-QAM classification
Published 2020“…Higher order cumulants are selected as feature set and Genetic Algorithm assisted Support Vector Machine (SVM) classifier is used for classification of M-QAM signals. …”
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72
A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
Published 2010“…In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. …”
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Nonlinear model predictive control of Hammerstein and Wiener modelsusing genetic algorithms
Published 2001“…In this paper a novel approach for the implementation of nonlinear MPC is proposed using genetic algorithms (GAs). The proposed method formulates the MPC as an optimization problem and genetic algorithms are used in the optimization process. …”
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75
Design of PSS and STATCOM-based damping stabilizers using genetic algorithms
Published 2006“…The design problem of STATCOM-based stabilizers is formulated as an optimization problem. Then, a real-coded genetic algorithm (RCGA) is employed to search for optimal stabilizer parameters. …”
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76
Simulated annealing and improved genetic algorithms for path testing. (c1997)
Published 1997Get full text
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masterThesis -
77
A distributed genetic algorithm for deterministic and stochastic labor scheduling problems
Published 1999“…Our distributed genetic algorithm operates in parallel on a network of message-passing workstations. …”
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78
Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
Published 2021“…Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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