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281
Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…The slime mould algorithm (SMA) gives good results in finding the best solutions to optimization problems. …”
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282
Evolutionary algorithms, simulated annealing and tabu search: a comparative study
Published 2020“…Abstract Evolutionary algorithms, simulated annealing (SA), and tabu search (TS) are general iterative algorithms for combinatorial optimization. …”
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283
A new multiobjective evolutionary algorithm forenvironmental/economic power dispatch
Published 2001“…In this paper, a new multiobjective evolutionary algorithm for environmental/economic power dispatch (EED) optimization problem is presented. …”
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284
Best Polynomial Harmony Search with Best β-Hill Climbing Algorithm
Published 2020“…The algorithm has been successfully applied to solve optimization problems in different domains. …”
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285
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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286
Scalable parallel algorithms for dynamic programming on tree decomposition. (c2017)
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masterThesis -
287
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288
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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289
A modified ant colony algorithm for evolutionary design of digital circuits
Published 2003“…In this paper, a multiobjective optimization of logic circuits based on a modified ant colony (ACO) algorithm is presented. …”
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290
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291
Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…Evolutionary algorithms have been effective in solving many search and optimization problems. …”
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292
A distributed genetic algorithm for deterministic and stochastic labor scheduling problems
Published 1999“…In this paper we present a unified formulation for these three labor scheduling problems and introduce a distributed genetic algorithm (DGA) that solves each of them. Our distributed genetic algorithm operates in parallel on a network of message-passing workstations. …”
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293
PERF solutions for distributed query optimization. (c1999)
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masterThesis -
294
Hybrid Cooperative Co-evolution for Large Scale Optimization
Published 2016“…In CC, multiple instances of the same evolutionary algorithm work in parallel, each optimizes a different subset of the problem in hand. …”
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295
Stochastic P-type/D-type iterative learning control algorithms
Published 2003“…This paper presents stochastic algorithms that compute optimal and sub-optimal learning gains for a P-type iterative learning control algorithm (ILC) for a class of discrete-time-varying linear systems. …”
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296
On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise
Published 2005“…Higher-Order Iterative Learning Control (HO-ILC) algorithms use past system control information from more than one past iterative cycle. …”
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conferenceObject -
297
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298
An Efficient Tabu Search Algorithm For The Single-Machine Mean Tardiness Problem
Published 2020“…In this paper, an efficient tabu search algorithm is prepared ibr solving the singlemachine mean tardiness problem. …”
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299
A stochastic iterative learning control algorithm with application to an induction motor
Published 2004“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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300
Genetic algorithm assisted support vector machine for M-QAM classification
Published 2020“…The classification accuracy is also compared with and without optimized classifier.…”
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