Wang Hongling

Genetic Algorithm Optimizing Neural Network for Short-Term Load Forecasting

Short-term load forecasting in power system is necessary for management and contrl of power system. A new method for short-term load forecasting was presented based on neural networks optimized by genetic algorithm (GA) is proposed in this paper, short-term load forecasting model for power system was setup as sample sets for Elman neural network(Elman NN), with GAs optimizing and Elman NNs dynamic feature, the higher forecasting pricision was realized and the simulation indicates the method is feasible and effective.

Study on Integrated Intelligent Control with Hierarchical Structure

The controlled plant can be tackled with intelligent control always a complex system and often can not be easily controlled with traditional control strategy, single intelligent control maybe inadequate for some complex system. So the integrated intelligent control is needed and often can combine with traditional control, with take advantages respectively. And intelligent control is scramble for it. In this paper, an integrated intelligent controller proposed with hierarchical structure, the principles of hierarchical was analyzed, the expert controller, fuzzy controller and neural network PID controller are designed, the integrated controller cooperate with each other by expert ratio divider, and applied to a control plant with the good control effect was proved.

Fault Diagnosis of Three Level Inverter Based on Improved Neural Networks

Inverter and related system were widely used in power electrical system and motor drive system to enhance the reliability and efficiency, the faults with various types and difficult to isolate with traditional techniques, so a new method based on neural network was presented. The neural-point clamped three level invert systems were analyzed and fault features were created by harmonica spectral analysis. The neural network was designed with algorithm programmed, with the fault diagnosis as inputs of neural network, by neural networks adaptive self-learning and take the outputs as judgment of fault types and then the faults occurred in inverter system was isolated . The new technique proposed in this paper was a theoretical foundation for invert system fault diagnosis and practical application for motor driver system, the simulation shows this method is effective and can be widely into inverted fault diagnosis system and relevant fault diagnosis system.

Application of Sensitivity Pruning Neural Networks in Surface Roughness Prediction

The surface roughness is a key parameters in high speed machining and often hard to control. The prediction model for surface roughness was created based on artificial neural networks which have strong non-linear modeling ability. The sample data collection method was analyzed and BP neural networks was designed, but the traditional BP neural networks has many shortcomings like easily step into local minimum, with weak generalization ability and the middle layer neuron are hard to determine, so the sensitivity pruning algorithm applied. The simulation shows the method is effective and can provide a guidance to optimize cutting parameters and control surface quality.

Depinning Dynamics of Two-Dimensional Charged Colloids on a Random Laser-Optical Substrate

Using Langevin simulations, we investigate the depinning dynamics of two-dimensional charged colloids on a random laser-optical substrate. With an increase in the strength of the substrate, we find a transition from crystal to smectic flows above the depinning. A power-law scaling relationship between average velocity and applied driving force could be obtained for both flows, and we find that the scaling exponents are no bigger than 1 for the crystal and are bigger than 1 for the smectic flows.

An IBM2 Description of the E(5) Symmetry in 134Ba and 108Pd

With the low-lying energy levels, E2 transition branching ratios and absolute transition rates of the 134Ba and 108Pd, are investigated in the neutron-proton interacting boson model (IBM2) which includes the quadrupole-quadrupole interaction between like bosons and the E(5) symmetry, it shows that the IBM2 can describe the nuclei at critical point of a phase transition well.