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In this paper, a two-layer network and distributed control method is proposed, where there is a top-layer communication network over a bottom-layer microgrid. The communication network consists of two subgraphs, in which the first is composed of all agents, while the second is only composed of controllable agents. The distributed control laws derived from the first subgraph guarantee the supply–demand...
In this paper, we consider a two-dimensional heterogeneous cellular network scenario consisting of one base station (BS) and some mobile stations (MSs) whose locations follow a Poisson point process (PPP). The MSs are equipped with multiple radio access interfaces including a cellular access interface and at least one short-range communication interface. We propose a nearest-neighbor cooperation communication...
In this paper, a novel direct adaptive NN control algorithm is proposed for a class of ship course autopilot with input saturation. Neural networks (NNs) are used to tackle unknown nonlinear function, and then an adaptive NN controller is constructed by combining Lyapunov function and the backstepping technique. By utilizing a special property of the affine term, the developed scheme avoids the controller...
The end effects of Hilbert-Huang transform are produced in the Empirical Mode Decomposition(EMD) and the Hilbert transform for Intrinsic Mode Functions(IMF), which have a badly effect on Hilbert-Huang transform. In order to overcome this problem, the multi-objective allocation Genetic Algorithm (GA) to solve the kernel parameters selection of Least Squares Support Vector Machine (LSSVM)(GLHHT) is...
In this paper, we first propose an Integration Wavelet Neural Network (I_WNN) based on spline wavelet functions for solving differential equations. Then the proposed method is verified successfully by solving two steady convection dominated diffusion problems and the numerical perturbation doesn't happen when the ratio of convective coefficient to diffusive coefficient is as high as 100. Moreover,...
An improved BP neural network model was presented by modifying the learning algorithm of the traditional BP neural network, based on the Levenberg-Marquardt algorithm, and was applied to the breakout prediction system in the continuous casting process. The results showed that the accuracy rate of the model for the temperature pattern of sticking breakout was 96.43%, and the quote rate was 100%, that...
Resources optimization of cross-layer is a typical multi-objective optimization problem. In this paper, an adaptive clone and neighbor selection algorithm is proposed to resolve optimization resources allocation in cognitive radio networks (CRNs). The algorithm uses the adaptive cloning operator, neighborhood search operator to improve the performance of algorithm. Simulation comparisons for typical...
Due to the fluctuation and complexity of the financial time series, it is difficult to use any single artificial technique to capture its non-stationary property and accurately describe its moving tendency. So a novel hybrid intelligent forecasting model based on empirical mode decomposition (EMD) and support vector regression (SVR) is proposed. EMD can adaptively decompose the complicated raw data...
A fuzzy neural network (FNN) multi-step prediction model based on singular spectrum analysis (SSA) and mean generating function (MGF) for summer precipitation has been developed in this paper. In the modeling process, the original standardized sample series of summer precipitation was denoised and reconstructed with SSA, the extended matrix of MGF of the reconstructed precipitation series (as the...
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