A new multimodulus blind equalization algorithm by Abrar, Shafayat

“…The phase-recovery and intersymbol interference optimization properties, exhibited by the proposed algorithm, are also discussed.…”
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Genetic algorithms applications in load frequency control by Abdel-Magid, Y.L.

“…This paper deals with the application of genetic algorithms for optimizing the parameters of conventional automatic generation control (AGC) systems. …”
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A SIMULATED ANNEALING ALGORITHM FOR THE CLUSTERING PROBLEM by Selim, S.Z.

“…In this paper we discuss the solution of the clustering problem usually solved by the K-means algorithm. The problem is known to have local minimum solutions which are usually what the K-means algorithm obtains. …”
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Adaptive bias simulated evolution algorithm for placement by Youssef, H.

“…Simulated Evolution (SE) is a general meta-heuristic for combinatorial optimization problems. A new solution is evolved from current solution by relocating some of the solution elements. …”
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A New Parallel Genetic Algorithm Model by Al-Somani, Turki F.

“…This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. …”
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Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

“…We formulate the testing problem as an optimization problem and use a simulated annealing (SA) metaheuristic algorithm to generate test cases as sequences of events while keeping the test suite size reasonable. …”
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Artificial neural network algorithms. (c1999) by Ramadan, Samer N.

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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm by Abu Zitar, Raed

“…The slime mould algorithm (SMA) gives good results in finding the best solutions to optimization problems. …”
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Scatter Search algorithm for Protein Structure Prediction by Mansour, Nashat

“…The results show that our algorithm is able to produce 3D structures with good sub-optimal energy values. …”
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Multiobjective Evolutionary Algorithms for Electric Power Dispatch Problem by Abido, M. A.

“…The potential and effectiveness of the newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) for solving a real-world power system multiobjective nonlinear optimization problem are comprehensively discussed and evaluated in this paper. …”
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Multiobjective evolutionary algorithms for electric power dispatch problem by Abido, M.A.

“…The potential and effectiveness of the newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) for solving a real-world power system multiobjective nonlinear optimization problem are comprehensively discussed and evaluated in this paper. …”
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Control of nonlinear dynamical systems using genetic algorithms by Al-Duwaish, H.N.

“…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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Evolutionary algorithms for VLSI multi-objective netlist partitioning by Sait, Sadiq M.

“…Further, we compared the results of the iterative heuristics with a modified FM algorithm, named PowerFM, which targets power optimization. …”
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Computational Experience On Four Algorithms For The Hard Clustering Problem by AlSultan, K.S.

“…Several algorithms have been developed to solve this problem which include the k-means algorithm, the simulated annealing algorithm, the tabu search algorithm, and the genetic algorithm. …”
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A new genetic algorithm approach for unit commitment by Mantawy, A.H.

“…This paper presents a new genetic algorithm approach to solve the unit commitment problem in electric power systems. …”
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Simultaneous stabilization of multimachine power systems viagenetic algorithms by Abdel-Magid, Y.L.

“…The problem of selecting the parameters of power system stabilizers which simultaneously stabilize this set of plants is converted to a simple optimization problem which is solved by a genetic algorithm with an eigenvalue-based objective function. …”
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Fuzzy simulated evolution algorithm for topology design of campusnetworks by Youssef, H.

“…The topology design of campus networks is a hard constrained combinatorial optimization problem. It consists of deciding the number, type, and location of the active network elements (nodes) and links. …”
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Fuzzy simulated evolution algorithm for VLSI cell placement by Sait, Sadiq M.

“…There has not been a consensus on how to accommodate all these (conflicting) requirements in the search for near optimal feasible solutions. In this paper, we present a fuzzy simulated evolution (FSE) algorithm to tackle this problem. …”
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Algorithmic Study of Online Multi-Facility Location Problems by Markarian, Christine

“…The latter is a worst-case analysis that compares the cost of the online algorithm to that of the optimal offline algorithm that is assumed to know all demands in advance. …”
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Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain by Farshad Rahimi Ghashghaei (20880995)

“…<p dir="ltr">This research presents an ensemble Reinforcement Learning (RL) approach that combines Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms to tackle quantum control problems. …”