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Artificial bee colony algorithm (ABC), which is inspired by the foraging behavior of honey bee swarm, is a biological-inspired optimization. It shows more effective than genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). However, ABC is good at exploration but poor at exploitation, and its convergence speed is also(More)
The extreme learning machine (ELM) is a novel single hidden layer feedforward neural network, which has the superiority in many aspects, especially in the training speed; however, there are still some shortages that restrict the further development of ELM, such as the perturbation and multicollinearity in the linear model. To the adverse effects caused by(More)
This paper proposes a novel artificial neural network called fast learning network (FLN). In FLN, input weights and hidden layer biases are randomly generated, and the weight values of the connection between the output layer and the input layer and the weight values connecting the output node and the input nodes are analytically determined based on least(More)
Accurately, forecasting of the flatness plays a highly significant role in the flatness theory and flatness control system, but it is quite difficult and complicated due to the nonlinear characteristics of flatness pattern recognition and lack of available observed data set. Recently, support vector regression (SVR) is being proved an effective machine(More)