New Improved Maximum Power Point Tracking Algorithm for Partially Shaded PV Systems

The paper presents new MPPT algorithm for partial shading of series connected PV cells/modules. In the shaded condition, there is a problem of decrease in the total output power of the PV system. The proposed algorithm aims to reduce this problem by active bypassing of the shaded cells. The algorithm senses the irradiance of each cell and performs calculation in order to decide if to actively bypass the shaded cell or not. Extensive simulation results proved that algorithm works and increases the output power under partial shading conditions. Furthermore, the algorithm becomes more efficient when the number of cells is increased.

Quantitative structure-property relationship study of the solubility of thiazolidine-4-carboxylic acid derivatives using ab initio and genetic algorithm-partial least squares

A quantitative structure-activity relationships （QSAR） study is suggested for the prediction of solubility of some thiazolidine-4- carboxylic acid derivatives in aqueous solution. Ab initio theory was used to calculate some quantum chemical descriptors including electrostatic potentials and local charges at each atom, HOMO and LUMO energies, etc. Modeling of the solubility of thiazolidine- 4-carboxylic acid derivatives as a function of molecular structures was established by means of the partial least squares （PLS）. The subset of descriptors, which resulted in the low prediction error, was selected by genetic algorithm. This model was applied for the prediction of the solubility of some thiazolidine-4-carboxylic acid derivatives, which were not in the modeling procedure. The relative errors of prediction lower that -4% was obtained by using GA-PLS method. The resulted model showed high prediction ability with RMSEP of 3.8836 and 2.9500 for PLS and GA-PLS models, respectively.

PARTIAL ELIMINTATION ALGORITHM FOR A LINEAR RECURRENCE SYSTEM R(n, m) OF ORDER m

This paper presents an algorithm for computing a linear recurrence system R(n, m) of order m for n equations on MIMD parallel system. This algorithm is not only easy to be programmed on a parallel computer system, but also reduces the data-waiting time due to compute-ahead strategy. The paper analyses how to achieve maximal load balancing when the algorithm is implemented on MIMD parallel system. By the end of the paper, an analysis on the speedup and parallel efficiency are given. The results indicate that the new parallel elimination algorithm has great improvement compared with the old ones.

AN ACCELERATION FOR THE EIGENSYSTEM REALIZATION ALGORITHM WITH PARTIAL SINGULAR VALUES DECOMPOSITION

The real-time identification of dynamic parameters is importantfor the control system of spacecraft. The eigensystme realizationalgorithm (ERA) is currently the typical method for such applica-tion. In order to identify the dynamic parameter of spacecraftrapidly and accurately, an accelerated ERA with a partial singularvalues decomposition (PSVD) algorithm is presented. In the PSVD, theHankel matrix is reduced to dual diagonal form first, and thentransformed into a tridiagonal matrix.

Partial Integrability Conditions and an Integrating Algorithm for Fully Rheonomous Affine Constraints

In this paper, integrability conditions and an integrating algorithm of fully rheonomous affine constraints (FRACs) for the partially integrable case are studied. First, some preliminaries on the FRACs are illustrated. Next, necessary and sufficient conditions on the partially integrable case for the FRACs are derived. Then, an integrating algorithm to calculate independent first integrals of the FRACs for the partially integrable case is derived. Moreover, the existence of an inverse function utilized in the algorithm is proven. After that, an example is presented for evaluation of the effectiveness of the proposed method. As a result, it turns out that the proposed integrating algorithm can easily calculate independent first integrals for given partially integrable FRACs, and thus this new algorithm is expected to be applied to various research fields.

Optimality Conditions and Algorithms for Direct Optimizing the Partial Differential Equations

New form of necessary conditions for optimality (NCO) is considered. They can be useful for design the direct infinite- dimensional optimization algorithms for systems described by partial differential equations (PDE). Appropriate algo-rithms for unconstrained minimizing a functional are considered and tested. To construct the algorithms, new form of NCO is used. Such approach demonstrates fast uniform convergence at optimal solution in infinite-dimensional space.

Partial关系上的聚合操作研究

现实世界中存在着许多非精确数据,在数据库系统中一般用Null值表示[2],表明目前不知道该值,显然这种表示丢失了许多信息.Grant总结定义了部分值(partial values)的概念来取代空值,使得关系表中的属性值可以不局限于不可分的原子.一个部分值被定义为一个可能值的有限集,在该有限集中只有一个值为'true”值.

Novel robust approach for constructing Mamdani-type fuzzy system based on PRM and subtractive clustering algorithm

A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator(partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy system, and an improved subtractive clustering algorithm in the fuzzy-rule-selecting phase. The weights obtained in PRM, which gives protection against noise and outliers, were incorporated into the potential measure of the subtractive cluster algorithm to enhance the robustness of the fuzzy rule cluster process, and a compact Mamdani-type fuzzy system was established after the parameters in the consequent parts of rules were re-estimated by partial least squares(PLS). The main characteristics of the new approach were its simplicity and ability to construct fuzzy system fast and robustly. Simulation and experiment results show that the proposed approach can achieve satisfactory results in various kinds of data domains with noise and outliers. Compared with D-SVD and ARRBFN, the proposed approach yields much fewer rules and less RMSE values.

ITERATIVE ALGORITHM FOR AXIALLY ACCELERATING STRINGS WITH INTEGRAL CONSTITUTIVE LAW

A numerical method is proposed to simulate the transverse vibrations of a viscoelastic moving string constituted by an integral law. In the numerical computation, the Galerkin method based on the Hermite functions is applied to discretize the state variables, and the Runge- Kutta method is applied to solve the resulting differential-integral equation system. A linear iterative process is designed to compute the integral terms at each time step, which makes the numerical method more efficient and accurate. As examples, nonlinear parametric vibrations of an axially moving viscoelastic string are analyzed.

Geometric precision evaluation methodology of multiple reference station network algorithms

To evaluate the performance of real time kinematic (RTK) network algorithms without applying actual measurements, a new method called geometric precision evaluation methodology (GPEM) based on covariance analysis was presented. Three types of multiple reference station interpolation algorithms, including partial derivation algorithm (PDA), linear interpolation algorithms (LIA) and least squares condition (LSC) were discussed and analyzed. The geometric dilution of precision (GDOP) was defined to describe the influence of the network geometry on the interpolation precision, and the different GDOP expressions of above-mentioned algorithms were deduced. In order to compare geometric precision characteristics among different multiple reference station network algorithms, a simulation was conducted, and the GDOP contours of these algorithms were enumerated. Finally, to confirm the validation of GPEM, an experiment was conducted using data from Unite State Continuously Operating Reference Stations (US-CORS), and the precision performances were calculated according to the real test data and GPEM, respectively. The results show that GPEM generates very accurate estimation of the performance compared to the real data test.

PREDICTOR-CORRECTOR ALGORITHMS FOR SOLVING GENERALIZED MIXED IMPLICIT QUASI-EQUILIBRIUM PROBLEMS

A new class of generalized mixed implicit quasi-equilibrium problems （GMIQEP） with four-functions is introduced and studied. The new class of equilibrium problems includes many known generalized equilibrium problems and generalized mixed implicit quasi-variational inequality problems as many special cases. By employing the auxiliary principle technique, some predictor-corrector iterative algorithms for solving the GMIQEP are suggested and analyzed. The convergence of the suggested algorithm only requires the continuity and the partially relaxed implicit strong monotonicity of the mappings

ROBUST PARTIAL INVERSE NETWORK FLOW PROBLEMS

In this paper,a new model for inverse network flow problems,robust partial inverse problem is presented. For a given partial solution,the robust partial inverse problem is to modify the coefficients optimally such that all full solutions containing the partial solution become optimal under new coefficients. It has been shown that the robust partial inverse spanning tree problem can be formulated as a combinatorial linear program,while the robust partial inverse minimum cut problem and the robust partial inverse assignment problem can be solved by combinatorial strongly polynomial algorithms.

Statistical Analysis for Constant-stress Partially Accelerated Life Test with Interval Censored Data

In this paper, a statistical analysis method is proposed to research life characteristics of products based on the partially accelerated life test. We discuss the statistical analysis for constant-stress partially accelerated life tests with Lomax distribution based on interval censored samples. The EM algorithm is used to obtain the maximum likelihood estimations(MLEs) and interval estimations for the shape parameter and acceleration factor.The average relative errors(AREs), mean square errors(MSEs), the confidence intervals for the parameters, and the influence of the sample size are discussed. The results show that the AREs and MSEs of the MLEs decrease with the increase of sample size. Finally, a simulation sample is used to estimate the reliability under different stress levels.

边缘协作环境下最小化完工时间任务调度方法

由于用户地理位置分布不均可能导致边缘服务器负载不均衡,难以为用户提供满意的服务质量。此外,边缘服务器可用资源有限,一些大任务可能难以全部卸载到边缘服务器。针对以上问题,利用多个边缘服务器之间的协作,结合任务部分卸载方式,提出一种边缘协作环境下最小化完工时间的任务调度方法。首先,结合边缘水平协作和任务部分卸载技术,考虑多用户多边缘服务器场景下用户和边缘服务器的位置关系,以最小化任务完工时间为目标,建立任务部分卸载调度模型;其次,提出基于改进分组教学优化算法的任务调度算法,联合优化边缘服务器计算资源分配、用户-边缘服务器关联决策、任务卸载比例以及执行位置决策,以最小化任务完工时间为目标,实现边缘计算环境下任务的高效调度;最后,通过实验将提出的任务调度算法与其他算法在多个指标下进行对比。实验结果表明,所提方法能够有效降低任务完工时间。

ROBUST ESTIMATION IN PARTIAL LINEAR MIXED MODEL FOR LONGITUDINAL DATA

In this article, robust generalized estimating equation for the analysis of partial linear mixed model for longitudinal data is used. The authors approximate the nonparametric function by a regression spline. Under some regular conditions, the asymptotic properties of the estimators are obtained. To avoid the computation of high-dimensional integral, a robust Monte Carlo Newton-Raphson algorithm is used. Some simulations are carried out to study the performance of the proposed robust estimators. In addition, the authors also study the robustness and the efficiency of the proposed estimators by simulation. Finally, two real longitudinal data sets are analyzed.

基于改进黏菌算法的光伏多峰值MPPT控制

针对传统最大功率点跟踪技术在局部遮阴等天气条件下存在无法追踪到全局最大功率点的问题,提出一种基于改进黏菌算法的MPPT控制。首先,对太阳电池模型及多峰值特性进行分析;其次,在黏菌算法中引入领导者策略和基于最优个体的凸透镜反向学习策略,在提高算法计算精度、收敛速度的同时克服了算法易“早熟”现象;最后,根据光伏阵列最大功率输出特性分别确定算法优化模型、初始化位置及重启机制。仿真与实验结果表明:基于改进黏菌算法的MPPT控制能快速、准确地跟踪到全局最大功率点,有效规避陷入局部最优问题,提高了光伏系统的转换效率。

A Novel Nonlinear Algorithm for Typhoon Cloud Image Enhancement

A novel nonlinear gray transform method is proposed to enhance the contrast of a typhoon cloud image.Generally,the typhoon cloud image obtained by a satellite cannot be directly used to make an accurate prediction of the typhoon＇s center or intensity because the contrast of the received typhoon cloud image may be bad.Our aim is to extrude the typhoon＇s eye in the typhoon cloud image.A normalized arc-tangent transformation operation is designed to enhance global contrast of the typhoon cloud image.Differential evolution algorithm is used to choose the optimal nonlinear transform parameter.Finally,geodesic activity contour model is used to extract the typhoon＇s eye to verify the performance of the proposed method.Experimental results show that the proposed method can efficiently enhance the global contrast of the typhoon cloud image while greatly extruding the typhoon＇s eye.

Design and FPGA-Implementation of Minimum PED Based K-Best Algorithm in MIMO Detector

Minimum Partial Euclidean Distance (MPED) based K-best algorithm is proposed to detect the best signal for MIMO (Multiple Input Multiple Output) detector. It is based on Breadth-first search method. The proposed algorithm is independent of the number of transmitting/receiving antennas and constellation size. It provides a high throughput and reduced Bit Error Rate (BER) with the performance close to Maximum Likelihood Detection (MLD) method. The main innovations are the nodes that are expanded and visited based on MPED algorithm and it keeps track of finally selecting the best candidates at each cycle. It allows its complexity to scale linearly with the modulation order. Using Quadrature Amplitude Modulation (QAM) the complex domain input signals are modulated and are converted into wavelet packets and these packets are transmitted using Additive White Gaussian Noise (AWGN) channel. Then from the number of received signals the best signal is detected using MPED based K-best algorithm. It provides the exact best node solution with reduced complexity. The pipelined VLSI architecture is the best suited for implementation because the expansion and sorting cores are data driven. The proposed method is implemented targeting Xilinx Virtex 5 device for a 4 × 4, 64-QAM system and it achieves throughput of 1.1 Gbps. The results of resource utilization are tabulated and compared with the existing algorithms.

一种高效16位有符号数乘法器设计

为了进一步优化乘法器的性能,提高乘法运算单元的运算速率,本文基于Radix 4 Booth算法和Wallace树压缩结构提出了一种改进的16位有符号数乘法器。其特点包括优化Radix 4 Booth编码方式,有效减小部分积选择电路的面积;改进部分积计算过程,通过优化取反加1的方法直接生成被乘数的相反数,同时采用经典的符号位补偿算法使得部分积阵列变得规整易压缩;提出一种新型42压缩器,采用单个全加器处理压缩器的中间进位,针对每行部分积不同的数据特征,细化处理了Wallace树压缩结构,提高了部分积的压缩效率。基于SMIC 180 nm标准单元库进行了综合与验证,结果表明本文所设计的乘法器关键路径延时为3.94 ns,面积为16246μm^(2),相比于现有的乘法器,本文乘法器的运算速率和综合性能都得到显著提升。

基于PSO-GWO算法的局部阴影光伏MPPT研究

针对在局部阴影条件下,光伏阵列的功率-电压特性曲线呈现多个峰值,传统群体智能优化存在收敛速度慢、振荡幅度大和易陷入局部最优等问题,提出一种基于PSO-GWO(Particle Swarm Optimization-Grey Wolf Optimization)算法的MPPT(Maximum Power Point Tracking)控制方法。该算法引入余弦规律变化的收敛因子,平衡GWO算法的全局搜索与局部搜索能力;引入PSO算法,提高灰狼个体与自身经验之间的信息交流。仿真结果表明,提出的PSO-GWO算法在局部阴影条件下不仅能快速收敛,而且功率输出震荡幅度更小,有效提升了局部遮阴条件下光伏阵列的最大功率跟踪效率和精度。