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Aiming at massive participation and open access education, Massive Open Online Courses (MOOCs) have attracted millions of learners over the past few years. However, the high dropout rate of learners is considered to be one of the most crucial factors that may hinder the development of MOOCs. To tackle this problem, statistical models have been developed to predict dropout behavior based on learner...
Web information, regarded as a useful repository including abundant data and knowledge, attracts much attention from researchers and practitioners, and has been used to analyze and forecast economic and social hotspots in recent years. In this paper, a novel neural network based forecasting method is proposed for the unemployment rate prediction using search engine query data. The empirical results...
Since the BP neural network algorithm has some unavoidable disadvantages, such as slowly converging speed and easily running into local minimum, the genetic algorithm and simulated annealing algorithm with the overall search capability have been put forward to optimize authority value and threshold value of BP nerve network. In this paper, a new neural network model which is optimized by genetic algorithm...
This paper improves the basic particle swarm optimization (PSO) algorithm with adaptive interior and acceleration coefficients which is called IPSO, and use the IPSO algorithm to optimize authority value and threshold value of BP nerve network. Thus IPSO-BP neural network algorithm model has been established and applied into the railway passenger volume forecast. The result shows that this model has...
Since the BP neural network algorithm has some unavoidable disadvantages, such as slowly converging speed and easily running into local infinitesimal, the genetic algorithm and simulated annealing algorithm with the overall search capability has been put forward to optimize authority value and threshold value of BP nerve network. In this paper, GA-SA-BP neural network algorithm model has been established...
Array-based bearing estimation often displays a threshold behavior, that is, below certain signal-to-noise ratio (SNR) the estimation mean-square error (MSE) increases dramatically. The error increase is known to be largely attributed to sidelobe ambiguities in signal field correlation along with estimation bias at low SNR. This paper investigates the bias-related contribution from the perspective...
The BP neural network algorithm has characteristics of slow convergence speed and local minimum value which could cause the loss of global optimal solution. In order to eliminate the shortcoming of BP neutral network algorithm, genetic algorithm is been put forward to optimize authority value and threshold value of BP nerve network. This paper establishes genetic neural network model. Study has been...
BP neural network has some shortcomings, such as low-precision solutions, slow search speed and easy convergence to the local minimum points. Ant colony algorithm(ACA) is a novel simulated evolutionary algorithm which accounts for rapid discovery of good solutions and easy to realize distributed computation. This paper establishes ant colony neural network model and applies in lithology recognition...
According to the limitations of traditional BP neural network algorithm, the method of adding momentum factor and changing learning rate is used to improve the traditional BP neural network algorithm and establish the new model of BP neural network which is applied to the urban air quality prediction. Practical application shows that improved BP neural network algorithm overcome the shortcomings like...
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