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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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Handover initiation algorithm in hierarchical macrocell/femtocell In LTE network / Abdul Azim Mad Diah by Mad Diah, Abdul Azim

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Reservoir system modelling using nondominated sorting genetic algorithm in the framework of climate change by Nurul Nadrah Aqilah, Tukimat

“…The statistics of climate change variation and the growth of evolution method inspire the development of a sustainable and long term reservoir operation system. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
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Sub-route reversal repair mechanism and differential evolution for urban transit network design problem by Tarajo, Buba Ahmed

“…As a further extension, a hybrid DE-PSO for the UTNDP is developed as a multiobjective combinatorial optimization that produces a set of routes that take into account the interest of users and operators for a given set of resource-and-service constraints. All proposed algorithms are executed using Python programming language, and the computational results show that the proposed algorithms improve the best-so-far results from the literature in most cases.…”
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Comparative Study of Economic Dispatch by Using Various Optimization Techniques by Hong, Mee Song, M. H., Sulaiman, Mohd Rusllim, Mohamed, Wong, Lo Ing

“…The optimization techniques used in this paper to do the comparison are Quadratic Programming (QP), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Differential Evolution (DE) and Genetic Algorithm (GA). …”
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Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game by Chang, Kee Tong

“…The proposed EC methods are Genetic Algorithm (GA), Differential Evolution (DE), Evolutionary Programming (EP), and Pareto-based Differential Evolution (PDE). …”
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Effect of multi-unit and multi-type DG installation using integrated optimization technique in distribution power system planning by Abdullah A., Musirin I., Othman M.M., Rahim S.R.A., Mansor M.H., Shaaya S.A., Aminuddin N., Goel L.K.