基于DSP的智能分布式无功补偿装置的设计

从工程实际的角度出发,提出一种新型的基于DSP的智能分布式无功补偿装置,能实现模拟量算法的采样计算和电容器在线监测及保护功能。与传统的分布式无功补偿装置相比,具有跟随负载无功需求进行动态补偿、电容器在线监测及谐波越限优化运行等特点。通过从投运前与投运后样机在现场的实时运行数据的数据对比可见,装置的补偿效果显著,且对谐波无明显放大作用。

Solving geometric constraints with genetic simulated annealing algorithm

This paper applies genetic simulated annealing algorithm (SAGA) to solving geometric constraint problems. This method makes full use of the advantages of SAGA and can handle under-/over- constraint problems naturally. It has advantages (due to its not being sensitive to the initial values) over the Newton-Raphson method, and its yielding of multiple solutions, is an advantage over other optimal methods for multi-solution constraint system. Our experiments have proved the robustness and efficiency of this method.

Modeling of Isomerization of C_8 Aromatics by Online Least Squares Support Vector Machine

The least squares support vector regression (LS-SVR) is usually used for the modeling of single output system, but it is not well suitable for the actual multi-input-multi-output system. The paper aims at the modeling of multi-output systems by LS-SVR. The multi-output LS-SVR is derived in detail. To avoid the inversion of large matrix, the recursive algorithm of the parameters is given, which makes the online algorithm of LS-SVR practical. Since the computing time increases with the number of training samples, the sparseness is studied based on the pro-jection of online LS-SVR. The residual of projection less than a threshold is omitted, so that a lot of samples are kept out of the training set and the sparseness is obtained. The standard LS-SVR, nonsparse online LS-SVR and sparse online LS-SVR with different threshold are used for modeling the isomerization of C8 aromatics. The root-mean-square-error (RMSE), number of support vectors and running time of three algorithms are compared and the result indicates that the performance of sparse online LS-SVR is more favorable.

Classification of hyperspectral remote sensing images based on simulated annealing genetic algorithm and multiple instance learning

A hybrid feature selection and classification strategy was proposed based on the simulated annealing genetic algonthrn and multiple instance learning （MIL）. The band selection method was proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then MIL was combined with image segmentation, clustering and support vector machine algorithms to classify hyperspectral image. The experimental results show that this proposed method can get high classification accuracy of 93.13% at small training samples and the weaknesses of the conventional methods are overcome.

Efficient Stochastic Simulation Algorithm for Chemically Reacting Systems Based on Support Vector Regression

The stochastic simulation algorithm （SSA） accurately depicts spatially homogeneous wellstirred chemically reacting systems with small populations of chemical species and properly represents noise, but it is often abandoned when modeling larger systems because of its computational complexity. In this work, a twin support vector regression based stochastic simulations algorithm （TS^3A） is proposed by combining the twin support vector regression and SSA, the former is a well-known robust regression method in machine learning. Numerical results indicate that this proposed algorithm can be applied to a wide range of chemically reacting systems and obtain significant improvements on efficiency and accuracy with fewer simulating runs over the existing methods.

Ab Initio Molecular Dynamics Simulation of Liquid Water with Fragmentbased Quantum Mechanical Approach under Periodic Boundary Conditions

In this study,we investigated the structural and dynamical properties of liquid water by using ab initio molecular dynamics simulation under periodic boundary conditions based on the fragment-based quantum mechanical approach.This study was carried out using the second-order Møller-Plesset perturbation theory(MP2)with the aug-cc-pVDZ basis set,which has been validated to be sufficiently accurate for describing water interactions.Diverse properties of liquid water,including radial distribution functions,diffusion coefficient,dipole moment,triplet oxygen-oxygen-oxygen angles,and hydrogen-bond structures,were simulated.This ab initio description leads to these properties in good agreement with experimental observations.This computational approach is general and transferable,providing a comprehensive framework for ab initio predictions of properties of condensed-phase matters.

Simulation of Flux Distribution in Central Metabolism of Saccharo-myces cerevisiae by Hybridized Genetic Algorithm

A scheme of investigating the intracellular metabolic fluxes in central metabolism of Saccharomyces cerevisiae based on isotope model and tracer experiment was developed. The metabolic model applied in this study includes the Embden-Meyerhof-Parnas pathway,the pentose phosphate pathway,the tricarboxylic acid cycle,CO2 anaplerotic reactions,ethanol and acetate formation,and pathways involved in amino acid synthesis. The approach of hybridized genetic algorithm combined with the sequential simplex technique was used to optimize a quadratic error function without the requirement of the information on the partial derivatives. The impact of some key pa-rameters on the algorithm was studied. This approach was proved to be rapid and numerically stable in the analysis of the central metabolism of S.cerevisiae.

Quantum Trajectory Approach to Molecular Dynamics Simulation with Surface Hopping

In this work we propose a quantum trajectory approach to the powerful molecular dynamics simulation with surface hopping, from an insight that an effective ＂observation＂ is actually implied in the simulation through tracking the forces experienced, just like checking the meter＇s result in quantum measurement process. This treatment can build the nonadiabatic surface hopping on a physical foundation, instead of the usual fictitious and conceptually inconsistent hopping algorithms. The effects and advantages of the proposed scheme are preliminarily illustrated by a two-surface model system.