基于RSKNN分类改进算法

RSKNN算法是K近邻算法的一种改进算法,该算法基于变精度粗糙集理论,能在保证一定分类精度的前提下,有效地降低分类样本的计算量,并且提高计算效率和分类精度．由于RSKNN算法对属性的依赖度较高,在分类时容易受到伪近邻的影响,导致RSKNN算法的分类精度受到一定程度的影响．针对存在问题,本文提出一种新颖的基于RSKNN算法的改进算法SMwRSKNN,该算法在RSKNN算法的基础上引入类别子空间的思想,以降低冗余属性和伪近邻对分类的影响．在UCI公共数据集上的实验结果表明,SMwRSKNN算法比RSKNN算法具有更高的分类精度．     

一种多目标置换流水车间调度问题的优化算法

针对最大完工时间最小和总流经时间最小的多目标置换流水车间调度问题(permutation flow shopscheduling problem, PFSP), 提出一种粒子群优化算法与变邻域搜索算法结合的混合粒子群优化(hybrid particleswarm optimization algorithm, HPSO)算法, 并使算法在集中搜索和分散搜索之间达到合理的平衡. 在该混合算法中,采用NEH 启发式算法进行种群初始化, 以提高初始解质量;运用随机键表示法设计基于升序排列规则(ranked-order-value, ROV), 将连续PSO 算法应用于置换流水车间调度问题;引入外部档案集存贮Pareto 解, 并采用强支配关系和聚集距离相结合的混合策略保证解集的分布性;采用Sigma 法和基于聚集距离的轮盘赌法进行全局最优解的选择;提出变邻域搜索算法, 对外部集中的Pareto 解作进一步地局部搜索. 最后, 运用提出的混合算法求解Taillard 基准测试集, 并将测试结果与SPEA2 算法进行比较, 验证该调度算法的有效性.     

Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence

Chlorophyll fluorescence is related to photosynthesis and can serve as a remote sensing proxy for estimating photosynthetic energy conversion and carbon uptake. Recent advances in sensor technology allow remote measurements of the sun-induced chlorophyll fluorescence signal (Fs) at leaf and canopy scale. The commonly used Fraunhofer Line Depth (FLD) principle exploits spectrally narrow atmospheric oxygen absorption bands and relates Fs to the difference of the absorption feature depth of a fluorescensing and a non-fluorescensing surface. However, due to the nature of these narrow bands, Fs retrieval results depend not only on vegetation species type or environmental conditions, but also on instrument technology and processing algorithms. Thus, an evaluation of all influencing factors and their separate quantification is required to further improve Fs retrieval and to allow a reproducible interpretation of Fs signals.Here we present a modeling study that isolates and quantifies the impacts of sensor characteristics, such as spectral sampling interval (SSI), spectral resolution (SR), signal to noise ratio (SNR), and spectral shift (SS) on the accuracy of Fs measurements in the oxygen A band centered at 760 nm (O₂-A). Modeled high resolution radiance spectra associated with known Fs were spectrally resampled, taking into consideration the various sensor properties. Fs was retrieved using the three most common FLD retrieval methods, namely the original FLD method (sFLD), the modified FLD (3FLD) and the improved FLD (iFLD). The analysis investigates parameter ranges, which are representative for field and airborne instruments currently used in Fs research (e.g., ASD FieldSpec, OceanOptics HR, AirFLEX, AISA, APEX, CASI, and MERIS).Our results show that the most important parameter affecting the retrieval accuracy is SNR, SR accounts for ≤ 40% of the error, the SSI for ≤ 12%, and SS for ≤ 7% of the error. A trade-off study revealed that high SR can partly compensate for low SNR. There is a strong interrelation between all parameters and the impact of specific parameters can compensate or amplify the influence of others. Hence, the combination of all parameters must be considered by the evaluation of sensors and their potential for Fs retrieval. In general, the standard FLD method strongly overestimates Fs, while 3FLD and iFLD provide a more accurate estimation of Fs. We conclude that technical sensor specifications and the retrieval methods cause a significant variability in retrieved Fs signals. Results are intended to be one relevant component of the total uncertainty budget of Fs retrieval and have to be considered in the interpretation of retrieved Fs signals.     

Interactive multiobjective fuzzy random programming through the level set-based probability model

This paper considers a multiobjective linear programming problem involving fuzzy random variable coefficients. A new fuzzy random programming model is proposed by extending the ideas of level set-based optimality and a stochastic programming model. The original problem involving fuzzy random variables is transformed into a deterministic equivalent problem through the proposed model. An interactive algorithm is provided to obtain a satisficing solution for a decision maker from among a set of newly defined Pareto optimal solutions. It is shown that an optimal solution of the problem to be solved iteratively in the interactive algorithm is analytically obtained by a combination of the bisection method and the simplex method.     

Online scheduling on unbounded parallel-batch machines to minimize maximum flow-time

We consider online scheduling on m unbounded parallel-batch machines to minimize maximum flow-time of the jobs. We show that no online algorithm can have a competitive ratio less than 1+αm, where αm is the positive root of α²+(m+1)α−1=0, and this lower bound is still valid even when all jobs have the same processing times. Then we provide an online algorithm of competitive ratio 1+1/m. When the jobs have the same processing times, we present a best possible online algorithm of competitive ratio 1+αm.     

Optimal semi-online algorithms for scheduling problems with reassignment on two identical machines

In this paper, we consider semi-online minimum makespan scheduling problem with reassignment on two identical machines. Two versions are discussed. In the first version, one can reassign the last job of one machine that is based on the problem proposed by Tan and Yu (2008) [1], in which case the last job of each machine is allowed to be reassigned. An optimal algorithm which has the same competitive ratio is presented. In the second version we consider the combination of the next two conditions: the total size of all jobs is known in advance and one can reassign the last job of one machine. For this problem an optimal algorithm with competitive ratio is also given.     

Broadband, red-edge information from satellites improves early stress detection in a New Mexico conifer woodland

Multiple plant stresses can affect the health, esthetic condition, and timber harvest value of conifer forests. To monitor spatial and temporal dynamic forest stress conditions, timely, accurate, and cost-effective information is needed that could be provided by remote sensing. Recently, satellite imagery has become available via the RapidEye satellite constellation to provide spectral information in five broad bands, including the red-edge region (690-730 nm) of the electromagnetic spectrum. We tested the hypothesis that broadband, red-edge satellite information improves early detection of stress (as manifest by shifts in foliar chlorophyll a + b) in a woodland ecosystem relative to other more commonly utilized band combinations of red, green, blue, and near infrared band reflectance spectra. We analyzed a temporally dense time series of 22 RapidEye scenes of a piñon-juniper woodland in central New Mexico acquired before and after stress was induced by girdling. We found that the Normalized Difference Red-Edge index (NDRE) allowed stress to be detected 13 days after girdling — between and 16 days earlier than broadband spectral indices such as the Normalized Difference Vegetation Index (NDVI) and Green NDVI traditionally used for satellite based forest health monitoring. We conclude that red-edge information has the potential to considerably improve forest stress monitoring from satellites and warrants further investigation in other forested ecosystems.     

A mixture of generalized latent variable models for mixed mode and heterogeneous data

In the behavioral, biomedical, and social-psychological sciences, mixed data types such as continuous, ordinal, count, and nominal are common. Subpopulations also often exist and contribute to heterogeneity in the data. In this paper, we propose a mixture of generalized latent variable models (GLVMs) to handle mixed types of heterogeneous data. Different link functions are specified to model data of multiple types. A Bayesian approach, together with the Markov chain Monte Carlo (MCMC) method, is used to conduct the analysis. A modified DIC is used for model selection of mixture components in the GLVMs. A simulation study shows that our proposed methodology performs satisfactorily. An application of mixture GLVM to a data set from the National Longitudinal Surveys of Youth (NLSY) is presented.     

一类新的广义形态学混合滤波器

传统形态学滤波器滤波后的图像灰度值产生偏移,滤波算子抑制噪声效果较差.基于双路对偶形态学算子的混合滤波器解决了传统形态学滤波器存在的灰度值偏移问题,但运算次数多,处理速度较慢.提出了广义混合交变序列滤波器,该滤波器继承了一般混合交变序列滤波器的重要性质,保持了对偶滤波器的强对称性,且运算量减少了一半.仿真实验表明,该混...     

一种6.9 ppm/℃92 dB PSRR基准电压源的设计

提出了一种利用简单结构实现高阶指数曲率补偿和高电源电压抑制比的带隙基准电压源。利用正温度系数的反向饱和电流IS和双极型晶体管正向导通时的电流增益β以及Trimming修条电阻实现温度补偿,同时采用Wilson电流镜和电压负反馈技术来提高PSRR。仿真结果表明,该基准电压源达到了6.9 ppm/℃的温度系数,低频时PSRR最高达92 dB和39.3 ppm/V的线性调整率。