Hierarchy-degree of Gray Relationship Ddecision of Land Investment Based on Cloud Model

The competition in the land market is drasticly increasing, which demands much higher scientificity and accuracy in the decision. The land investment decision system is a non-linear gray system and the traditional appraisal methods have some limit in appraising it. It uses cloud model and the uncertain illation based on the cloud model, translates the qualitative appraisal of the factors level into quantitative scores, achieves the transition between a linguistic term of a qualitative concept and its numerical representation ; and further merges the degree of gray relationship theory to appraise the comprehensive level of the objects. So the new decision mode is set up. Through an example analysis and contrast study, the validity of the method is validated. The application of cloud theory in the decision field will affirmatively improve the decision level.     

Effects of Nonregular Spatial Distribution of Plants on Yield per Area: A Theoretical Approach with Applications to Winter Oilseed Rape (Brassica napus L.)

In this study a stochastic approach, based on several simplifying assumptions, is developed that allows an estimation of the effects of nonregular spatial patterns of the distribution of individual plants on yield per area. In this approach, two random variables were attached to each individual plant: single plant yield and individual space per plant. The latter can be estimated, for example, by the area of Thiessen polygons. Yield per area is calculated theoretically by the expectation (=mean) of the ratio between individual yield and area. Based on the logarithmic relationship between single plant yield and individual space per plant, yield per area can be broken down into three additive terms: the first term depends only on the mean of individual plant areas, while the second depends on their mean and variance simultaneously. This second term is the product of the variance and a factor which depends only on the mean. The third term is a function of the mean and of higher order (≥ 3) central moments of a fractional linear transformation of individual plant area. Finally, these theoretical concepts were applied to 17 experimental data sets of three cultivars of winter oilseed rape (Brassica napus L.) with measurements for single plant yields and individual areas for the Thiessen polygon tesselations. Since yield per area is theoretically defined by the expectation of the ratio between individual yield and area, it is estimated by the arithmetic mean of the individual yield/area‐ratios. The agreement between this estimate and the sum of the estimated terms from the aforementioned additive decomposition of yield per area is particularly good. For the 17 data sets, percentages for these additive terms of approximately 71.4 % up to 98.4 % (mean: 89.0 %) for the first term, 1.6 % up to 20.0 % (mean: 9.8 %) for the second term and 0 % up to 8.7 % (mean: 1.2 %) for the third term are obtained. As a consequence it may be concluded, that yield per area can be explained mainly by dependencies on the means of individual plant areas while the variance of individual plant spaces is of only minor importance. The effect of the third term is insignificant. These results clearly indicate an answer to the main issue raised in the paper, namely the importance of seeding density as opposed to seeding accuracy/uniformity: nonuniformity is of limited influence and seeding density is the main correlate of yield/area. Seed placement accuracy of seeding technology therefore plays an only minor role.     

Experimental Results on the Effects of Nonregular Spatial Patterns of Plants on Yield per Area

Based on several simplifying assumptions, a stochastic approach was developed which allows an estimation of the effects of nonregular spatial patterns of the distribution of individual plants on yield per area (F). In this approach, two random variables were attached to each plant: single plant yield (E) and individual space per plant (A). The latter was estimated by the area of Thiessen polygons. Yield per area was calculated theoretically by the expectation of the ratio E / A. Appropriate approximations of this expectation depend on the means (ē and ā), coefficients of variation (vE and vA) of E and A and their correlation (rEA). Yield per area can be decomposed into two additive terms: the first term gives the commonly used estimate ē/ā— or h(ā)/ā if a functional relationship between E and A is assumed: E = h(A). In this study, the two relationships E = k1 + k2 · ln A and E = A/(k3 + k4A) were used (with appropriately chosen constants k1, k2, k3, and k4). The second term in the decomposition of F can be interpreted as the effect of variable individual plant spaces on yield per area. In this paper, all theoretical concepts and results were applied to 17 experimental data sets of three cultivars of winter oilseed rape (Brassica napus L.). Single plant yields (E) and individual plant areas (A) were positively correlated with correlation coefficients from 0.64 up to 0.91. The ranges for both coefficients of variation were similar: 0.27 ≤ vE ≤ 0.65 and 0.28 ≤ vA ≤ 0.59. One obtains no significant differences in the goodness-of-fit for both tested relationships between E and A although the logarithmic relationship seems to be slightly superior. For only three data sets one obtains negative values for the percentage of the second term in the decomposition of F. This indicates an overestimation of yield per area by the commonly used estimates h(ā)/ā and ē/ā, respectively. These overestimations, however, are less than 5 %. In all other cases with positive values for the second term the yield per area is underestimated by the common estimates. For almost all data sets, however, the percentages of F which are explained by the common estimates are much larger than 90 %.     

Uncertain reasoning model for the rocket safety decision system

In view of the complexity of the measuring environment and uncertainty of the a prior knowledge for rocket aviation,a rocket safety control system based on uncertainty reasoning is proposed.The uncertain representation and processing of the knowledge in expert systems are established according to the characteristics of the parameters .Following the characteristics of the decision rules and decision procudure,the reasoning control strategy is studied and the method for conflict resolving strategy and searching strategy is proposed.Then,the uncertain matching rules and the feasibility degree delivering method are expressed,and the decision-making network and the rule-based uncertainty reseaoning model were constructed.Simulation experiments show that this system can acquire the craft launching information quickly and accurately,which greatly improves the reliability and authenticity of safety control decision for rocket aviation,and can control the rocket aviating state effectively.     

Illumination compensation of color video for driver fatigue monitor

A robust method to compensation illumination of driver video color image to enhance image quality has been proposed. Firstly, the original image is decomposed into high-frequency image and low-frequency image based on spatial image decomposition. The illumination information is completely contained in the low-frequency image. Next, low-frequency image is compensated by using Retinex approach which can brighten the darker area. Then, the compensated low-frequency image and high-frequency image are synthesized. Finally, new image is obtained by illumination balance of synthesized image. Results show that the algorithm has better results compared with the traditional algorithm.     

天水地区暴雨特征、环流形势及概念模型分析

为提高天水地区暴雨预报及服务能力,利用1965—2011年天水地区地面观测资料以及Micaps实况资料,运用统计学方法、天气学原理以及中尺度分析技术,对天水地区暴雨进行分析。结果表明：天水地区暴雨近47年来年均发生频次约为2.38次,呈略减少趋势,幅度为每10年下降0.135次,但变化趋势不明显;暴雨发生时间主要分布在每年的4—10月,集中在7—8月;暴雨空间分布自渭北区—河谷区—关山区依次增多;天水地区暴雨分布与地形有一定的关系;天水暴雨的主要环流形势有4种,即：西低东高型、副高西北侧西南气流型、低涡切变型以及副高控制型;天水地区最常见的暴雨环流形势是副高西北侧西南气流型,西低东高型、低涡切变型以及副高控制型暴雨所占比例相对较少;各形势下的暴雨主要影响系统、动力以及热力条件各有不同。     

水田防护林空间密度分布研究

水田防护林是保护水田免受风灾的一道绿色屏障,水田防护林空间密度分布可以体现区域水田分布的疏密程度,研究水田防护林空间密度分布对水田防护林建设规划和水田产量研究都有着重要的意义。本研究以吉林省前郭灌区为研究区域,对灌区内水田防护林的空间密度分布进行了研究。以遥感影像为基础数据对灌区水田防护林进行监督分类,经过验证kappa系数达到0.87,根据分类结果提取水田防护林总面积为110.945 km2,总周长为4998.095 km。利用网格法对灌区防护林数据进行空间密度分析,得出灌区水田防护林空间密度分布图,根据密度分布现状进行了分析得出结论,前郭灌区水田防护林分布不均匀,防护林重点分布在灌区南部地区,北部新开水田区防护林分布极少,对灌区水稻产量构成了不利的影响。     

The spatial distribution estimation of Interference temperature based on kriging method in cognitive radio

In order to resolve the problems of the traditional interference temperature estimation methods, such as unclear spatial characteristics, inaccurate estimation of spatial distribution, and the insufficient use of spectrum resources, this paper proposes an estimation method which utilizes the interference temperature sample values obtained by wireless sensors distribute in space to estimate the interference temperature in the total area. This method makes use of the geo-statistical interpolation method of Kriging to calculate the interference temperature data and obtain the 3-dimensional distribution of the interference temperature in the area. Kriging interpolation method is based on the variogram and structure analysis theory, makes optimal estimation of the variables in area. Simulation results demonstrate that the proposed method can estimate the spatial distribution of interference temperature in the interested area more accurately and the spatial spectrum utilization is improved.     

Fusion method for infrared and visible light images based on image segmentation and stationary wavelet transform

A novel image fusion method based on image segmentation and stationary wavelet transform (SWT) is proposed to improve the visual effect of fused infrared and visible light images. Infrared image is firstly separated into object and background region utilizing Otsu combined with edge detection. Then a multiresolution decomposition using SWT is made to the background region of the infrared image and the visible light image. Neighborhood spatial frequency and absolute value are adopted as fusion rules in low-frequency and high-frequency coefficients. The background fused image is reconstructed by inverse SWT. The final infrared and visible light fused image is obtained by fusing the background fused image and the object region of infrared image base on weighted fusion rule. The experimental results show that the object information of the infrared image is obviously highlighted and the scene information of the visible light image is well represented. The visual effect of fused image is improved efficiently by utilizing the proposed method. The proposed method works better than the traditional Laplacian Pyramid and wavelet transform fusion algorithms in terms of standard deviation, comentropy and mutual information. Experimental results verify its effectiveness.     

Analysis of the Spatial Variability in Cotton Growth Conditions based on Digital Imaging

Digital images of cotton canopy growth information, which was determined using the grid sampling method to obtain the parameter Hue of HIS color system in conventional light conditions, were used to examine the spatial distribution characteristics of the canopy image H value and the relationship between the digital image H value and agronomic traits. We used these data to obtain information on cotton growth on June 21, 2014, then analyzed the spatial variation characteristics of cotton growth in the field. We found that the spatial distribution of cotton canopy digital image H value was moderately correlated with space, and the semi-variogram function model was spherical. In addition, we found that there was a logarithmic relationship between the H value and Leaf Area Index（LAI） (R² = 0.8123), which suggests that the canopy digital image H value is a potentially reliable index to describe cotton growth across a cotton field. These results can provide guidance for improved production methods, and also lay a foundation for collection of field information and rapid detection methods for precision agriculture.     

基于排水单元的流域农业面源污染时空分异性研究

为了揭示流域内各排水单元农业面源N、P污染的总量和组成特征,揭示各排水单元间农业面源污染的时空变异特征,以湖北四湖流域为例,选取流域内24个排水单元,运用ENVI 4.7和GIS技术提取出研究区土地利用现状,并建立基础数据库,通过对排水单元出水口水体的多时段定点采样测试,分析四湖流域排水单元农业面源污染的时空变化特征。结果表明：各排水单元面源污染空间分布格局总体上呈现上、下区排水单元污染较轻、中区表现严重的态势,这与流域内湿地和旱地等土地利用分布格局有关。在时间变异方面,农业面源年内变异明显,TN、TP在不同季节存在着显著差异,主要表现在冬、春季的浓度明显高于夏、秋季,这与流域内降水和径流的季节性差异有关。     

基于小麦籽粒高光谱特征的品种鉴别研究

为探究高光谱成像技术在小麦籽粒品种鉴别等的研究,以15种品种已知的小麦籽粒为对象,分别采集样品的光谱和图像信息。运用主成分分析法优选三个特征波长(447nm、615nm、955nm),提取特征波长下小麦籽粒图像的形态特征(面积、周长、圆度、长轴长度、短轴长度)和纹理特征(均值、标准差、熵)。应用Bayes判别分析法进行多元统计分析,建立判别函数判别回代准确率为99.9%,交叉验证的准确率为98%,模型的判别效果良好。研究表明利用高光谱成像技术结合Bayes判别分析的方法可用于小麦籽粒品种的鉴别。     

储粮害虫图像的灰关联分析方法研究

对储粮害虫进行实时监测是非常必要的，其中基于图像识别的检测是目前研究较多的一种方法。本文提出了一种基于灰关联分析的图像边缘检测的新算法，并将其应用于储粮害虫图像的边缘检测，计算表明，该方法能有效地检测粮虫图像的边缘信息。     

Image Restoration Using Adopted Regularization Technology

Image restoration is aimed to recover the original scene from its degraded version. Based on the customary regularization technology and the property of the human visual systems, a new method for image restoration based on adopted regularization technology is presented. This technique is achieved by adopting the parameters of the residual term and the regularization term of each pixel in different part of the image. We can get the parameters of each pixel by computing the local variance at each point. Simulation results demonstrate that the method improves restored image quality and does not slow down the convergence of the evaluation function.     

Irrigation Water Management for Efficient Water Use in Mulched Onion

Caused by the necessarily imperfect seed placement accuracy of sowing machines and, additionally, caused by many other biotic and abiotic factors, the resulting plant stands exhibit nonregular spatial distributions of its plants. Based on several simplifying assumptions, a stochastic approach is developed which allows an estimation of the effects of nonregular spatial patterns on yield per area. In this approach, two random variables are attached to each plant: single plant yield E and individual space A . The latter is estimated by the area of Thiessen polygons. Yield per area, calculated by the expectation of the ratio E/A , can be approximately expressed dependent on the means ( Ē and Ā ) and coefficients of variation ( v _E and v _A ) of E and A and their correlation ( r _EA ). In relation to the commonly used estimate Ē/Ā for yield per area, one obtains yield decreases if v _A / v _E  <  r _EA . This inequality, however, will be usually valid in the field of applications. The theoretical approaches and results were applied to three experimental data sets for drilled seeds of winter oilseed rape ( Brassica napus L.) (plant density: 60 plants m⁻², row distance: 10 cm). These data sets are characterized by different accuracies of longitudinal distributions within rows (58 %, 101 %, 150 %): yield depression increases with an increasing variability of plant distances within rows.     

Hierarchy Group Decision-making Method of Evaluation of Residential Areas Architecture Design Schemes

For incarnating the effects of the preference of the potential users of residential areas or decision makers on the evaluation of architecture design schemes,a two hierarchy multi-attribute group decision model is established.How to obtain the decision matrix of expert evaluation incarnates the influence of difference of professional knowledge among experts on decision.Multi-attribute decision making method based on uncertain linguistic assessment is used to determine the users' preference on schemes.The weight of attributes is determined by a optimization model that makes the difference of attribute assessment between expert and user minimum,and those weights are used in expert decision.This can enable the model to reflect correctly the actual situation of such decision making question.     

Image edge detection algorithm in fuzzy domain

An image edge detection algorithm in fuzzy domain is proposed, which combines adaptive fuzzy enhancement and multi direction fuzzy morphology to detect the edges of fuzzy image. The adaptive fuzzy enhancement method enhances the fuzzy image within blocks with sliding windows to avoid losses of the real edges resulting from enhancing with single threshold for the whole image and lead strong adaptive ability to image region variance. The multi direction fuzzy mathematical morphology operates on the enhanced fuzzy image with structure elements of multiple different directions to extract the real edges with directionality and restrain non directional noise. Experiments show the algorithm can detect fuzzy image edge effectively with strong antinoise ability.     

基于无人机多光谱的华北平原花铃期棉花叶片SPAD建模方法研究

华北平原地区棉花叶片SPAD光谱特征有待探明,其最适宜建模方法亦有待研究。笔者针对华北平原棉区,基于无人机多光谱探索其叶片SPAD光谱特征和最佳建模方法。以德州市夏津县大李庄棉区为研究区,利用无人机获取棉花花铃期的多光谱图像,同步测定棉花叶片SPAD值;对原始光谱进行预处理并组合构建光谱指数,进而采用相关分析筛选出6个棉花SPAD特征光谱指数;分别采用BP神经网络(BPNN)、多元逐步回归(MSR)和支持向量机(SVM)方法构建棉花SPAD值定量分析模型,并对模型验证、对比,优选最佳模型和建模方法,进而定量分析研究区棉花叶片SPAD空间分布。结果表明:棉花叶片SPAD的特征波段为红光和红边波段;入选模型的特征光谱指数为r、r*reg、(reg-r)/(reg+r)、r-g、r/g、$\sqrt{r^{2}+g^{2}}$;对比3种建模方法,BPNN模型精度最高,其建模集R²、RMSE分别为0.747、4.568,验证集R²、RMSE、RPD分别为0.758、4.142、2.135,确定为棉花叶片SPAD的最佳模型。基于BP神经网络模型进行棉花叶片SPAD的空间分布反演,反演值与实测值具有高度一致性,拟合结果较好。BP神经网络可以作为基于无人机多光谱的华北平原棉花叶片SPAD建模的优选方法,该研究可促进棉田定量遥感和棉花长势监测。     

鲜香菇外部品质计算机视觉检测与分级研究

根据鲜香菇图像特点和分级标准,运用计算机视觉技术和神经网络算法对香菇进行自动检测与分级。采用掩模去背景、中值滤波、边缘亮度补偿等技术对图像进行处理。选取香菇菇盖最大直径、圆形度、色调均值及缺陷区域总面积与香菇图像总面积的比值作为鲜香菇分级的特征参数。通过BP神经网络建立了特征参数与鲜香菇等级之间的关系模型,试验结果表明,其预测识别结果达到94.2%。