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The grid is hierarchical in three parts whose functions are quite different. First, the transmission system's role is to transport energy into high voltage from production centers to consumption areas and distribution network directly supplies large industrial consumers and supplying the average and low voltage consumers, with the latest advances in industry and Technological the need for electricity...
Evolutionary algorithms are efficient algorithms for solving the most complex optimization problems of the current era. Differential Evolution (DE) is a simple population based evolutionary algorithm under this category. As shown in literature, c omparative to exploration of the search space, DE is less capable of exploiting the existing solutions. Therefore, DE is very much expected to skip the true...
Developing efficient evolutionary algorithms for solving learning-based real-parameter single objective optimization is a very challenging and essential task in many real applications. This task involves finding the best optimal solution with least computational cost, avoiding premature convergence. This paper proposes a new efficient Differential Evolution algorithm with success-based parameter adaptation...
Differential Evolution (DE) is a popular and simple to implement population based stochastic evolutionary algorithm which is used to solve complex optimization problems. In DE, the variation in solutions during the solution search process is controlled by two significant control parameters, namely scale factor (F) and crossover probability (CR). These parameters play important role for balancing the...
The ordinary differential evolution (DE) algorithm employs real-valued vectors as genotypes. The author previously proposed an extension of DE which can handle interval-valued genotypes. In this paper, the proposed method is applied to evolution of neural networks with interval connection weights and biases. Experimental results show that the interval DE can evolve neural networks which model interval...
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