Application of Projection Pursuit Evaluation Model Based on Real-Coded Accelerating Genetic Algorithm in Evaluating Wetland Soil Quality Variations in the Sanjiang Plain, China

A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded accelerating genetic algorithm (RAGA), the projection direction is optimized and multi-dimensional indexes are converted into low-dimensional space. Classification of wetland soils and evaluationof wetland soil quality variations are realized by pursuing optimum projection direction and projection func-tion value. Therefore, by adopting this new method, any possible human interference can be avoided andsound results can be achieved in researching quality changes and classification of wetland soils.

Low side lobe pattern synthesis using projection method with genetic algorithm for truncated cone conformal phased arrays

A hybrid method for synthesizing antenna＇s three dimensional （3D） pattern is proposed to obtain the low sidelobe feature of truncated cone conformal phased arrays. In this method, the elements of truncated cone conformal phased arrays are projected to the tangent plane in one generatrix of the truncated cone. Then two dimensional （2D） Chebyshev amplitude distribution optimization is respectively used in two mutual vertical directions of the tangent plane. According to the location of the elements, the excitation current amplitude distribution of each element on the conformal structure is derived reversely, then the excitation current amplitude is further optimized by using the genetic algorithm （GA）. A truncated cone problem with 8x8 elements on it, and a 3D pattern desired side lobe level （SLL） up to 35 dB, is studied. By using the hybrid method, the optimal goal is accomplished with acceptable CPU time, which indicates that this hybrid method for the low sidelobe synthesis is feasible.

The continuous wavelet projections algorithm: A practical spectral-feature-mining approach for crop detection

Spectroscopy can be used for detecting crop characteristics. A goal of crop spectrum analysis is to extract effective features from spectral data for establishing a detection model. An ideal spectral feature set should have high sensitivity to target parameters but low information redundancy among features.However, feature-selection methods that satisfy both requirements are lacking. To address this issue,in this study, a novel method, the continuous wavelet projections algorithm(CWPA), was developed,which has advantages of both continuous wavelet analysis(CWA) and the successive projections algorithm(SPA) for generating optimal spectral feature set for crop detection. Three datasets collected for crop stress detection and retrieval of biochemical properties were used to validate the CWPA under both classification and regression scenarios. The CWPA generated a feature set with fewer features yet achieving accuracy comparable to or even higher than those of CWA and SPA. With only two to three features identified by CWPA, an overall accuracy of 98% in classifying tea plant stresses was achieved, and high coefficients of determination were obtained in retrieving corn leaf chlorophyll content(R^(2)= 0.8521)and equivalent water thickness(R^(2)= 0.9508). The mechanism of the CWPA ensures that the novel algorithm discovers the most sensitive features while retaining complementarity among features. Its ability to reduce the data dimension suggests its potential for crop monitoring and phenotyping with hyperspectral data.

Approximate subgradient projection algorithm for convex feasibility problem

An ε-subgradient projection algorithm for solving a convex feasibility problem is presented.Based on the iterative projection methods and the notion of ε-subgradient,a series of special projection hyperplanes is established.Moreover,compared with the existing projection hyperplanes methods with subgradient,the proposed hyperplanes are interactive with ε,and their ranges are more larger.The convergence of the proposed algorithm is given under some mild conditions,and the validity of the algorithm is proved by the numerical test.

The application of projection pursuit classification in the process of strategy selection and evaluation based on the real coded accelerating genetic algorithm

During the process of enterprises＇ strategy evaluation and selection, there are many evaluating indicators, and among them there are some potential correlations and conflicts. Thus it poses the problems to the decision-makers how to conduct correct evaluation on a business and how to make strategy adjustment and selection according to the evaluation. Based on the qualitative and quantitative method, the paper introduces the Projection Pursuit Classification （PPC） model based on the Real-coded Accelerating Genetic Algorithm （RAGA） into the process of enterprises＇ strategy evaluation and selection. The characteristic of PPC model is that it ultimately overcomes the influence of the proportion of subjectivity and avoids precocious convergence, thus providing a new objective method for strategy evaluation and selection by pursuing the most objective strategy evaluation to make the relatively sensible strategy portfolio and action.

An algorithm for computed tomography image reconstruction from limited-view projections

With the development of the compressive sensing theory, the image reconstruction from the projections viewed in limited angles is one of the hot problems in the research of computed tomography technology. This paper develops an iterative algorithm for image reconstruction, which can fit the most cases. This method gives an image reconstruction flow with the difference image vector, which is based on the concept that the difference image vector between the reconstructed and the reference image is sparse enough. Then the l1-norm minimization method is used to reconstruct the difference vector to recover the image for flat subjects in limited angles. The algorithm has been tested with a thin planar phantom and a real object in limited-view projection data. Moreover, all the studies showed the satisfactory results in accuracy at a rather high reconstruction speed.

Hybrid alternate projection algorithm and its application for practical conformal array pattern synthesis

Based on the fabricated 12-element cavity-backed microstrip sector cylinder array,a novel hybrid alternate projection algorithm（HAPA）,which combines analytical method with numerical techniques effectively,is proposed for synthesizing the pattern of practical conformal array.The algorithm applies the variable direction aperture projection method with mutual coupling correction techniques to provide the good initial excitations of elements to the enhanced alternate projection algorithm（EAPA）.In order to do further optimization,which improves the convergent speed of the algorithm significantly.Finally,the HAPA has been applied to the fabricated sector cylinder array with mutual coupling considered.The results of synthesized patterns,such as low sidelobe with null points formed pattern,beam scanning with low sidelobe pattern and the shaped beam pattern are presented.It demonstrates the validity of HAPA in practical conformal array synthesis.

Research and Implementation for License Plate Recognition Based on Improved Projection Algorithm

This paper analyzes and dissertates the discrete wavelet transform and improved projection algorithm in four kernel stages （image preprocessing, license plate localization, character segmentation, license plate recognition, i.e.） of license plate recognition system in detail. At last, it gives some conclusions and suggestions on future research.

A PROJECTION-TYPE ALGORITHM FOR SOLVING GENERALIZED MIXED VARIATIONAL INEQUALITIES

We propose a projection-type algorithm for generalized mixed variational in- equality problem in Euclidean space Rn. We establish the convergence theorem for the pro- posed algorithm, provided the multi-valued mapping is continuous and f-pseudomonotone with nonempty compact convex values on dom（f）, where f ： Rn --RU{＋∞} is a proper func- tion. The algorithm presented in this paper generalize and improve some known algorithms in literatures. Preliminary computational experience is also reported.

Projection pursuit model of vehicle emission on air pollution at intersections based on the improved bat algorithm

The projection pursuit model is used to study the assessment of air pollution caused by vehicle emissions at intersections. Based on the analysis of the characteristics and regularities of vehicle emissions at intersections, a vehicle emission model based on projection pursuit is established, and the bat algorithm is used to solve the optimization function. The research results show that the projection pursuit model can not only measure the air pollution of vehicle emissions at intersections, but also effectively evaluate the level of vehicle exhaust emissions at intersections. Taking the air pollution caused by vehicle emissions at intersections as the research object and considering the influence factors of vehicle emissions on air pollution comprehensively, the evaluation index system of vehicle emissions at intersections on air pollution is constructed. Based on large data analysis, a prediction model of air pollution caused by vehicle emissions at intersections is constructed, and an improved bat algorithm is used to realize the assessment process. The application results show that the prediction model of vehicle emissions at intersections can define the degree of air pollution caused by vehicle emissions, and it has good guiding significance and practical value for solving the problem of air pollution caused by vehicle emissions.

New hybrid inertial CQ projection algorithms with line-search process for the split feasibility problem

In this paper, we propose two hybrid inertial CQ projection algorithms with linesearch process for the split feasibility problem. Based on the hybrid CQ projection algorithm, we firstly add the inertial term into the iteration to accelerate the convergence of the algorithm, and adopt flexible rules for selecting the stepsize and the shrinking projection region, which makes an optimal stepsize available at each iteration. The shrinking projection region is the intersection of three sets, which are the set C and two hyperplanes. Furthermore, we modify the Armijo-type line-search step in the presented algorithm to get a new algorithm.The algorithms are shown to be convergent under certain mild assumptions. Besides, numerical examples are given to show that the proposed algorithms have better performance than the general CQ algorithm.

New Methodology for Direct Algorithms in Russell Projection ＂Stereographic Projection＂

Projections of geodetic are important for all countries all over the world, where using system coordinates for solving any problems in measurements of surveying works. Russell projection is one of projections used in some countries. Direct algorithms in this projection use two methods. The first method uses partial differential equation, which is not after six orders in the series. While, the second method uses traditional series （exponential series）, which is very difficult and requires complex statistical analysis. New methodology has been applied for direct algorithms in Russell projection using general law of unlimited algorithms by simple method.

BEAM BROADENING SYNTHESIS FOR SAR ANTENNA ARRAY BASED ON PROJECTION MATRIX ALGORITHM

A new beam broadening synthesis technique for Synthetic Aperture Radar(SAR) antenna array, namely Projection Matrix Algorithm(PMA) is presented. The theory of PMA is introduced firstly, and then the iterative renewed manner is improved to resolve the unbalance problem under amplitude and phase control. In order to validate the algorithm correct and effective, an actual engineering application example is investigated. The beam synthesis results of 1.0~4.5 times broadening under the phase only control and the amplitude and phase control using improved PMA are given. The results show that the beam directivity, the beam broadening, and the side-lobe level requirements were met. It is demonstrated that the improved PMA was effective and feasible for SAR application.

A GEOMETRIC ALGORITHM FOR TILTED-CAMERA PERSPECTIVE PROJECTION AND THE COMPARISON WITH EXTERNAL PERSPECTIVE PROJECTION

A geometric algorithm for Tilted-Camera Perspective（TCP）projec-tion is proposed in this paper based on the principle of perspective projection.Ac-cording to that,the difference between TCP projection and External Perspective（EXP）projection is analyzed.It is put forward prerequisites making these twoprojections were compatible,and some examples are given.

求解粒子群粒度分布的改进Projection算法

针对在激光粒度分布反演中由于迭代算法的迭代步长选取不当致使反演结果存在严重展宽和拖尾的问题,提出一种调整迭代步长的方法应用于Projection算法来提高测量精度。该方法首先基于测距相似度原理得到光能分布列向量与光能系数矩阵行向量之间的相似度曲线,经滤波和归一化处理后得到被测粒子群的预测粒度分布;然后根据预测粒度分布结果确定迭代步长的大小。使用本文提出的改进Projection算法测量国家标准物质GWB(E)120046的D50误差为-0.6%、D10误差为-1.1%、D90误差为-0.6%,测量GWB(E)120041与GWB(E)120049混合标准物质的光能对数误差为2.167。测量结果表明,该算法可有效地提高算法的抗噪声能力、测量精度和分辨率。

Projection算法在粒子尺寸测量中的实验研究

提出了 projection迭代算法在激光粒度测量中的算法停止迭代条件 ,提高了 Projec-tion算法在实际粒子尺寸测量中的适用性 .通过对国家标准物质研究中心提供的微粒标准物质及其混合液的实际测试实验 ,证实了

Projection算法在光谱法检测上皮组织发育异常中的应用

由散射光谱推知上皮组织发育异常属于一类反问题,此问题可转化为反演上皮组织细胞核的粒径变化。对上皮组织细胞核的单次散射偏振光谱进行数值模拟,并采用Projection迭代算法反演细胞核的粒径分布信息。Projection迭代算法将方程组的解看成是多维空间的一个点,通过不断求解各超平面上的投影点而逼近真值。数值计算表明,Projection算法对于粒径呈单峰、双峰分布细胞核均有良好的反演精度,采用该法有望增加光谱法上皮组织发育异常诊断的灵敏度。

基于Projection算法的激光粒度测试反演算法研究

针对Projection迭代反演算法对噪声极其敏感,及在实际应用中造成粒度测量失真的问题,引入Vondrak数据平滑算法对Projection反演进行平滑处理。借助Visual C++6.0开发平台,编写测试软件对算法应用进行了仿真研究。通过分析比较平滑处理前后的反演结果,得出Vondrak数据平滑处理算法的引入有效提高了Projection反演的抗干扰性能。实验结果表明:基于Vondrak数据平滑处理的Projection反演结果能够反映粒度的真实分布,满足现代粉体工业粒度测量的稳定可靠、精度高、抗干扰能力强的要求。

DUAL-SPARSITY PRESERVING PROJECTION

Sparsity preserving projection（SPP） is a popular graph-based dimensionality reduction（DR） method, which has been successfully applied to solve face recognition recently. SPP contains natural discriminating information by preserving sparse reconstruction relationship of data sets. However, SPP suffers from the fact that every new feature learned from data sets is linear combinations of all the original features, which often makes it difficult to interpret the results. To address this issue, a novel DR method called dual-sparsity preserving projection （DSPP） is proposed to further impose sparsity constraints on the projection directions of SPP. Specifically, the proposed method casts the projection function learning of SPP into a regression-type optimization problem, and then the sparse projections can be efficiently computed by the related lasso algorithm. Experimental results from face databases demonstrate the effectiveness of the proposed algorithm.

Improved differential evolution algorithm for resource-constrained project scheduling problem

An improved differential evolution（IDE）algorithm that adopts a novel mutation strategy to speed up the convergence rate is introduced to solve the resource-constrained project scheduling problem（RCPSP）with the objective of minimizing project duration Activities priorities for scheduling are represented by individual vectors and a senal scheme is utilized to transform the individual-represented priorities to a feasible schedule according to the precedence and resource constraints so as to be evaluated.To investigate the performance of the IDE-based approach for the RCPSP,it is compared against the meta-heuristic methods of hybrid genetic algorithm（HGA）,particle swarm optimization（PSO） and several well selected heuristics.The results show that the proposed scheduling method is better than general heuristic rules and is able to obtain the same optimal result as the HGA and PSO approaches but more efficient than the two algorithms.