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Researches on computer application to musical creation are actively performed in artificial intelligence. In this paper, we propose a hybrid method that adopts BP neural network for evaluation of emotions in music and genetic algorithm as an appropriate method for nominating creativity. Compared to other GAs used in this field, emotional element is used and combined with some musical rules as fitness...
Traditional Modeling Methods (such as PCA, PLS, Neural Network) have the disadvantages of low determination precision and long analysis time resulted by lots of wavelength points in Near Infrared Spectroscopy (NIRS). Considering the global search ability of genetic algorithm, this paper proposed a new back-propagation neural network model which selects parts of the spectroscopy wavelength points as...
The BP feed-forward neural network is popular in solving many non-linear multivariate and complex problems. The most important problem with neural network is to decide optimal structure and parameter settings. Literature presents a multitude of methods but there is no rigorous and accurate analytical method. This paper presents the hybrid approach of genetic algorithm and neural network computing...
This work presents the synthesis of crossed dipole frequency selective surfaces (FSSs) using a genetic algorithm (GA) whose fitness function is composed by an artificial neural network (ANN). The ANN model was trained by the resilient backpropagation (RPROP) algorithm, through the use of accurate data provided by a parametric study developed to investigate some of the geometric parameters of the FSSs...
A neural network alpha-beta-gamma filters optimized by an improved genetic algorithm (GA) was presented. In this new algorithm, a special fitness function on the basis of the tracker performance and adapted crossover and mutation probability were designed. So that premature convergence can be avoided, and the population diversity can be maintained. The improved GA ensures that the obtained parameters...
The imbalanced data sets are often encountered in business, industry and real life applications. In this paper, the novel fitness function in genetic algorithms to optimize neural networks is proposed for solving the classification problems in imbalanced data sets. Not only the parameters of neural networks but also the links-pruning between neurons are regarded as an optimization problem in this...
According to the complexity and coupling of steam turbine-generator, the diagnosis model based on improved genetic algorithm and BP network is proposed in this paper. First, the time factor is considered in the fitness function of genetic algorithm, then use the adaptive crossover rate and mutation rate to improve the genetic algorithm. As soon as the improved genetic algorithm optimizes the initial...
Op-amp based scheme design of a fixed weight application of the backpropagation neural network is presented in this work. In this design, the most important limitations in op-amp utilization are investigated for design purposes. These limitations played an important role to obstruct the traditional learning phase. To encompass these limitations, sl-CONE model with its powerful learning algorithm is...
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