Spatial quality evaluation for drinking water based on GIS and ant colony clustering algorithm

To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used. Drinking water samples from 29 wells in Zhenping County, China, were collected and analyzed. 35 parameters on water quality were selected, such as chloride concentration, sulphate concentration, total hardness, nitrate concentration, fluoride concentration, turbidity, pH, chromium concentration, COD, bacterium amount, total coliforms and color. The best spatial interpolation methods for the 35 parameters were found and selected from all types of interpolation methods in GIS environment according to the minimum cross-validation errors. The ACCA was improved through three strategies, namely mixed distance function, average similitude degree and probability conversion functions. Then, the ACCA was carried out to obtain different water quality grades in the GIS environment. In the end, the result from the ACCA was compared with those from the competitive Hopfield neural network(CHNN) to validate the feasibility and effectiveness of the ACCA according to three evaluation indexes, which are stochastic sampling method, pixel amount and convergence speed. It is shown that the spatial water quality grades obtained from the ACCA were more effective, accurate and intelligent than those obtained from the CHNN.

Employment Quality EvaluationModel Based on Hybrid Intelligent Algorithm

In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes the related research work of employment quality evaluation,establishes the employment quality evaluation index system,collects the index data,and normalizes the index data;Then,the weight value of employment quality evaluation index is determined by Grey relational analysis method,and some unimportant indexes are removed;Finally,the employment quality evaluation model is established by using fuzzy cluster analysis algorithm,and compared with other employment quality evaluation models.The test results show that the employment quality evaluation accuracy of the design model exceeds 93%,the employment quality evaluation error can meet the requirements of practical application,and the employment quality evaluation effect is much better than the comparison model.The comparison test verifies the superiority of the model.

Water Quality Evaluation Model Based on Principal Component Analysis and Information Entropy:Application in Jinshui River

水质评价对决策者决定水的使用功效尤为重要。水质综合评价系统中涉及到大量因子与指标,因子之间相互作用,致使水质的评价工作相对困难。主成分分析法可以消除因子间的相关性,因而被广泛应用于水质评价,但其忽略了数据离散程度的问题。熵值法则考虑了数据的离散特点。为更好地进行水质的综合评价,本文提出把主成分分析法和熵值法结合起来确定指标权重的方法,建立了水质评价模型,并采用该模型对郑州市金水河再生水2009年的水质情况进行评价,将评价结果与单独采用主成分分析或熵值法的结果进行了比较。结果表明了该方法的可行性与实用性,能够为非常规水资源利用提供理论依据和决策参考。

Evaluation and classification of residential greenbelt quality based on factor analysis & clustering analysis:An example of Xinxiang City,China

Five factors expressing greenbelt quality and one factor expressing quantity were adopted for evaluation of the residential greenbelt, and the AHP （Analytical Hierarchy Process） method was used to determine the value of factors. Thirty residential areas were selected as the samples. Two principal components were extracted and their expression was constructed by method of factor anlysis, therefore, quality evaluation of residential greenbelt was obtained. The accuracy of the function and implement quality classification toward the residential greenbelts in Xinxiang City were validated by clustering analysis method. The results showed that the greenbelt quality of fourteen residential areas was higher than the average level, of which eleven were newly-built residential areas. The 30 residential areas were classified into three types according to their greenbelt features and their formation by clustering analysis method. Finally rational proposal basing on aforesaid evaluating results was proposed for construction and renewal of residential greenbelt, upon which directive basis was provided for construction and renewal of residential greenbelt.

The Main Evaluation Indicators for the Quality of Fruit Radish

The aim of this study was to establish a scientific evaluation system for fruit radish quality. 8 quality indicators were measured for23 varieties,such as Meinong,Qiaotouqing and Chunbulao. The indicators included root weight,root shape index,water content,crispness,soluble solids,crude fiber,isothiocyanate and vitamin C. These data were analyzed by variation correlation analysis,principal component analysis and system cluster analysis. 23 varieties of fruit radish were analyzed by variation correlation; 8 indicators were compressed into 6 integrated variables using principal component analysis. Finally,the main evaluation indicators of fruit radish were determined by using cluster analysis and correlation analysis. The results indicated that the range of variation coefficient was from 1. 64%-89. 99%. Water content,crispness,soluble solids,crude fiber,isothiocyanate were the important components of fruit radish quality,playing a major role in the quality. These 8indicators were closely related and relatively independent. Water content was significantly and positively correlated with crispness; soluble solids and crude fiber were significantly and negatively related to vitamin C; crispness was significantly and positively correlated with crude fiber and vitamin C. Based on the above results,4 representative indicators were used for evaluating fruit radish quality,that is water content,crispness,soluble solids,crude fiber,which could reflect the most information of fruit radish quality.

Evaluation, prediction, and protection of water quality in Danjiangkou Reservoir, China

The water quality in the Danjiangkou Reservoir has attracted considerable attention from the Chinese public and government since the announcement of the Middle Route of the South to North Water Diversion Project （SNWDP）, which commenced transferring water in 2014. Integrated research on the evaluation, prediction, and protection of water quality in the Danjiangkou Reservoir was carried out in this study in order to improve environmental management. Based on 120 water samples, wherein 17 water quality indices were measured at 20 monitoring sites, a single factor evaluation method was used to evaluate the current status of water quality. The results show that the main indices influencing the water quality in the Danjiangkou Reservoir are total phosphorus （TP）, permanganate index （CODM,）, dissolved oxygen （DO）, and five-day biochemical oxygen demand （BODs）, and the concentrations of TP, BODs, ammonia nitrogen （NH3--N）, CODM,, DO, and anionic surfactant （Surfa） do not reach the specified standard levels in the tributaries. Seasonal Mann--Kendall tests indicated that the CODMn concentration shows a highly significant increasing trend, and the TP concentration shows a significant increasing trend in the Danjiangkou Reservoir. The distribution of the main water quality indices in the Danjiangkou Reservoir was predicted using a two-dimensional water quality numerical model, and showed that the sphere of influence from the tributaries can spread across half of the Han Reservoir if the pollutants are not controlled. Cluster analysis （CA） results suggest that the Shending River is heavily polluted, that the Jianghe, Sihe, and Jianhe rivers are moderately polluted, and that they should be the focus of environmental remediation.

Spatial analysis and evaluation of a coal deposit by coupling AHP & GIS techniques

Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification regarding their sustainable exploitation,when compared to other coal deposits or competitive fuels,which may be used as alternative solutions for electricity generation.In this paper,a method for spatial analysis and evaluation of a lignite deposit is proposed,by creating four spatial key indicators via GIS analysis,which are then aggregated by applying a weighted linear combination.The analytical hierarchy process is applied to estimate the relative weights of the indicators,in order to perform a weighted cartographic overlay.Through the synthesis of the indicators,an overall,total spatial quality indicator is calculated.The weighted analysis was shown to be more effective compared to the unweighted one,because it can provide more reliable results regarding the exploitation of the examined lignite deposit.The implementation of GIS-based analytical hierarchy process in spatial analysis and evaluation of lignite deposits,in terms of sustainable exploitation,demonstrates that this method can be extensively applied for evaluating the economic potential of mineral deposits.

Construction and Application of Combined Evaluation Model of Regional Water Quality Plan

[Objective] The aim was to study the construction and application of combined evaluation model of regional water quality plan. [Meth- od] By dint of layer analysis, subjective and objective model of entropy evaluation, the water quality plan in Jinghe was evaluated. Combined evalu- ation model based on information entropy were constructed, and considering the single model evaluation result, the optimal water quality plan was selected. [ Result] The combination weight result suggested that COD amount was the most essential indicator in water quality plan and embodied the importance of water environment protection, which met basic objective of environment protection and social, economic effects. Combined evalu- ation indicated that in the sixteen plans, plan 16 was of highest comprehensive evaluation value, and can be considered as optimum water quality plan. [ Conclusion] Combined evaluation model can effectively list the advantages of each evaluation model and improve the dependability of water quality plan, and provided a new research idea for the optimal evaluation of water pollution control plan.

云南不同品种核桃果实品质分析与综合评价

为了探究云南主栽核桃和薄壳山核桃果实的品质评价指标,选取27个核桃品种果实,对矿质元素、蛋白脂、粗脂肪等12个营养指标进行变异和相关性分析,并采用主成分和聚类分析方法,进行分类与综合评价。结果表明:12个营养指标的含量变异较为丰富,变异系数的变化范围为5%~83%,其中VC变异系数最大,粗脂肪变异系数最小;9种矿质元素平均含量从高到低依次为:K>P>Mg>Ca>Mn>Na>Fe>Zn>Cu,蛋白质含量均值为15.62%,脂肪含量均值为68.63%,VC的平均含量为4.66 mg/100 g;相关性分析表明,12个营养指标之间,P、Fe、Mg、Ca、Cu均与蛋白质呈极显著(P<0.01)正相关;主成分分析进行综合评价筛选出品质最佳的核桃品种为‘香茶’‘永平’‘晚熟’和‘小圆果’,薄壳山核桃中品种‘卡多’综合表现较好;聚类分析结果显示,可将其分为两大类,即富含矿质元素类群和高脂肪含量类群;相关性分析和主成分分析结果显示,K、Fe、Mg、Ca、Cu元素、蛋白质、脂肪为评价云南不同品种核桃品质的关键性指标。薄壳山核桃适合榨油,22种主栽核桃适合直接食用或开发富矿质元素和高蛋白的功能饮料。研究明确了云南核桃品质评价的关键指标并探明品质特性,提供科学分类方法,为云南核桃品质评价体系的构建奠定理论依据。

基于主成分分析和聚类分析的李子果实品质综合评价

为了解不同品种李子的品质特性,本文选取12个品种李子作为研究对象,分别从外观、理化及糖酸组成等方面对果实品质进行了对比分析,同时采用主成分分析和聚类分析对李子品质性状进行综合评价。结果表明,不同品种李子外观、理化和糖酸组成等指标均表现出丰富的多样性。糖酸组成、色泽、单果重、果实密度和果形指数等是评价李子综合品质的关键性指标。12个品种中‘紫皇’(ZH)‘圣雪珀’(SXP)‘爱丽丝’(ALS)‘香李’(XL)‘香甜李’(XTL)5个品种综合评分为正值,品质较好。其中,ZH和SXP品质特征为出汁率、可溶性固形物、总糖含量及色泽品质高;ALS品质特征为总糖、总甜度、甜酸比和糖酸比最高;XL和XTL品质特征为可溶性固形物含量、糖酸比、甜酸比高,但出汁率低。该研究结果可作为不同用途李子品种筛选的重要参考依据。

基于主成分分析和聚类分析麝香草酚微胶囊/魔芋葡甘露聚糖/低酰基结冷胶可食性复合涂膜对蓝莓品质的综合评价

该研究旨在建立综合评价麝香草酚微胶囊/魔芋葡甘露聚糖/低酰基结冷胶(thymol microcapsule/konjac glucomannan/low-acyl gellan gum,TKL)可食性复合涂膜对蓝莓保鲜效果的方法。以晚熟蓝莓品种‘巴尔德温’为试材,从感官、生理生化、营养成分、色泽和质构等角度,采用主成分分析(principal component analysis,PCA)、聚类分析、相关性分析等综合评价TKL采前喷涂对蓝莓贮藏品质的影响。结果表明,TKL涂膜处理减缓了蓝莓贮藏过程中感官、果形指数、总酸、硬度、L^(*)、b^(*)、H^(*)和弹性的下降;抑制了失重率、腐烂率、丙二醛、a^(*)、C^(*)值的增加;维持较高的可溶性固形物、总酚、总黄酮、花青素含量、咀嚼性和回复性,从而减缓了蓝莓品质的劣变。PCA分析得到2个主成分,累计方差贡献率为86.90%。PCA得分与感官评价拟合呈极显著正相关(P<0.01)。聚类分析显示,TKL涂膜处理21~56 d的蓝莓品质与对照组7~35 d聚类同一类。TKL涂膜将贮藏期从42 d延长到63 d。PCA与聚类分析结合,可更准确地评价TKL涂膜对蓝莓采后综合质量的影响,为TKL涂膜在采后果实的保鲜应用提供理论依据。

基于化学计量学和指纹图谱的辽宁道地药材北五味子质量评价研究

目的 采用指纹图谱与化学计量学相结合的方法,评价辽宁岫岩产北五味子的质量。方法 采用HPLC法,柱温30℃,流速1 mL/min,流动相采用水-乙腈梯度洗脱,检测波长220 nm,对10批辽宁岫岩五味子基地生产的北五味子建立指纹图谱,运用聚类分析(hierarchical cluster analysis, HCA)、主成分分析(principal component analysis, PCA)及正交偏最小二乘法-判别分析(orthogonal partial least squares-discriminant analysis, OPLS-DA)进行化学模式识别分析。结果 建立了岫岩产北五味子的指纹图谱,相似度为0.970^0.999,共标定了29个共有峰,指认了14个成分;HCA分析10批北五味子可分为2类;PCA共得到6个主要成分,其累计方差贡献率为95.5%;OPLS-DA表明五味子甲素、戈米辛G、五味子丙素、五味子醇乙等11个成分可能是影响北五味子质量的差异性标志物。结论 研究所建立的指纹图谱结合化学模式识别分析,方法准确、稳定、可靠,可用于北五味子药材的质量控制研究。

基于G1-EW云模型的火工品保障人员能力素质评估

针对火工品保障人员能力素质评估问题,根据全面质量管理理论和过程安全管理理论,在指标设置过程中采用灰色关联分析法对指标进行筛选,构建了较为科学的评估指标体系。通过博弈论思想将序关系分析法与灰色关联分析法(G1)联合使用求解的指标权重与熵权法(entropy weight,EW)所求权重进行组合,使权重设置更合理,运用云模型实现对评估指标的定量分析与定性分析的综合考虑,最终建立了一种基于G1-EW云模型的火工品保障人员能力素质评估模型。实例验证结果证明了该模型合理、有效,对火工品保障人员能力素质提升具有一定的指导作用。

不同品种新疆大果沙枣果实品质综合评价

本研究利用新疆大果沙枣果实外观指标和有效营养成分指标,结合主成分分析和聚类分析对果实品质进行综合评价,旨在为新疆大果沙枣的进一步开发利用提供理论依据。结果表明,不同品种大果沙枣果实外观品质存在显著性差异;根据主成分分析法,综合评价结果为‘红铃’(3#)>‘红玉’(8#)>‘金莎’(2#)>‘金皇后2’(26#)>‘巴楚1’(5#)>‘金皇后’(6#)>‘白沙甜’(7#)>‘雅丰’(1#)>‘红铃2’(33#),3#、8#和2#表现优良,可重点进行繁育推广及开发利用。根据聚类分析,将9个品种的大果沙枣分为3类;第1类为3#品种,主要特征为固酸比、单宁和总酚高,蛋白质、粗纤维低,可用作制作糕点及高档果汁、饮料等;第2类为2#和8#品种,主要特征为可食率高,总黄酮、原花青素含量高,单宁和总酚也高于均值,可用作深加工,提取其有效功能性营养成分,用于保健、医疗等;其余品种均属于第3类,各项指标较为平均,果实可鲜食及加工,也可用作生态林等。

30个鲜食枣种质果实品质综合评价

为筛选果实综合性状良好的鲜食枣品种,以30个不同鲜食枣种质为研究对象,选取8个外观品质指标和6个内在品质指标,采用相关性分析、主成分分析、聚类分析方法综合评价鲜食枣果实品质。结果表明,不同枣种质的果实品质性状差异明显,变异系数为9.10%~29.95%,b^(*)值的变异系数最大,L^(*)值的变异系数最小。主成分分析得到特征值大于1的4个主成分,累计方差贡献率为81.08%,根据主成分分析结果进行计算并排序,综合评价前5位为Z2-5、N-2、Z-6、灵武长枣4号、N-3,果实品质较好。结合相关性和聚类分析,将鲜食枣果实品质指标简化为6个,为b^(*)值、可滴定酸含量、单果重、果形指数、维生素C含量、可溶性固形物含量。研究结果为鲜食枣种质资源的评价和品种选育提供了参考。

基于组合赋权与灰色聚类的枪弹品质评估

针对枪弹品质无法定量评估、枪弹数据利用率低等问题,提出一种基于主客观组合赋权与灰色聚类的枪弹品质评估模型。该模型采用线性加权将主客观赋权法所得权重相结合,以提高评估方法中指标赋权的科学性,构造隶属度函数,再利用灰色聚类的方法得出综合影响因数,从而得到枪弹的品质判断结果。以12.7 mm穿甲燃烧弹开展评估,并进行立靶密集度试验。结果表明,该方法具有较好的区分度,密集度指标R100,I类(12.77 cm)约域类(15.02 cm)约芋类(18.92 cm),验证了方法的有效性。

一测多评法测定法制半夏曲中11种成分含量及其GRA、EW-TOPSIS质量评价

目的采用一测多评(QAMS)法同时测定法制半夏曲中肌苷、鸟苷、腺苷等11种成分含量,并建立其灰色关联度分析(GRA)联合熵权逼近理想解排序分析法(EW-TOPSIS)综合质量评价方法。方法采用Shimadzu C 18色谱柱;乙腈-0.5%醋酸为流动相,梯度洗脱,流速1.0 mL·min-1;检测波长254和290 nm。以对甲氧基肉桂酸乙酯为内参比物质,计算其他10个成分的相对校正因子(RCF),测定各成分含量。采用GRA联合EW-TOPSIS模型对法制半夏曲进行综合质量评价。结果法制半夏曲中11种成分在一定浓度范围内线性关系良好,相关系数均>0.999;平均加样回收率96.94%~100.12%(RSD<2.0%,n=9);QAMS与外标法(ESM)实测值无明显差异。GRA模型相对关联度0.2903~0.6187,EW-TOPSIS模型相对接近度0.2114~0.6343;GRA和EW-TOPSIS模型综合评价结果基本一致。结论QAMS法便捷、准确,可用于法制半夏曲多指标成分定量控制,GRA联合EW-TOPSIS模型可用于法制半夏曲综合质量评价。

基于主成分和聚类分析的安徽大豆品种与豆腐加工特性研究

以安徽省20个大豆品种为研究对象,测定大豆主要理化成分(粗蛋白、可溶性蛋白质、粗脂肪、水分等)及制备豆腐品质参数(湿基得率、含水量、保水性、硬度等),采用相关性分析、主成分分析及聚类分析方法对大豆品种进行综合品质评价。结果表明:大豆主要理化成分与豆腐加工品质存在一定的相关性。主成分分析得到4个主成分因子,其累计方差贡献率达72.783%,综合得分前三的品种为涡豆5、皖豆21551和皖宿1019。聚类分析将20种大豆分为Ⅰ、Ⅱ、Ⅲ、Ⅳ、Ⅴ、Ⅵ类,每类所含品种分别为7、3、1、7、1、1种。主成分分析得到的3个品种被归为第Ⅱ类,这类大豆粗蛋白含量高、豆腐湿基得率高。涡豆5、皖豆21551和皖宿1019这3个品种适宜豆腐的加工。

不同采收期不同品种莲藕的营养品质变化规律及评价

目的探究不同采收期不同品种莲藕的营养成分和活性成分的变化规律。方法选取5个采收期的4个品种莲藕,测定蛋白质、淀粉等指标。采用主成分分析和聚类分析进行综合评价,并建立莲藕品质评价模型。结果在采收期内,莲藕淀粉含量呈现先上升后下降再上升的趋势,可溶性糖的变化趋势与其相反;总酚含量整体呈现先上升后下降的趋势;蛋白质、膳食纤维等指标呈现不同的变化规律。主成分分析法提取出PC_(1)、PC_(2)、PC_(3)3个主成分因子,特征值依次为2.274、1.933、1.023,累积方差贡献率达87.170%。不溶性膳食纤维、可溶性膳食纤维、可溶性总糖、淀粉、总酚和总黄酮6个指标可以用来综合评价莲藕营养品质。综合评价发现,9月采收的八月粉,10月的鄂莲6号,2月的鄂莲10号和鄂莲11号,营养品质较好,优于其他采收期。3月采收的4个品种莲藕的综合营养品质较低。结论在采收期内,4个品种莲藕的营养物质动态规律存在一定差异。基于主成分分析和聚类分析的分析方法能够科学评价不同采收期莲藕的综合营养品质,为莲藕育种、加工等提供支撑。

不同莲藕品种的营养品质分析与评价

探究不同莲藕品种的营养成分和活性成分,为莲藕品种筛选、加工利用及产品开发等提供支撑。通过测定7个莲藕品种的10个成分指标,采用主成分分析和聚类分析对不同莲藕品种营养品质进行综合评价,并建立莲藕营养品质评价模型。结果表明,大白胖的蛋白质含量(w,后同)(10.50%)和不溶性膳食纤维含量(12.13%)最高,鄂莲6号的脂肪含量(0.98%)最高,544的可溶性膳食纤维含量(6.35%)最高,八月粉的淀粉含量(65.59%)最高;莲藕整体呈现高淀粉、低脂肪且富含膳食纤维和蛋白质的特征。主成分分析结果表明,淀粉、脂肪、总酚和总黄酮含量累积贡献率达95.172%,可以用这4个主成分来综合评价莲藕营养品质的优劣,并建立莲藕综合营养品质评价模型F=0.692F1+0.308F2;综合得分表明鄂莲5号的品质最佳,小白胖的品质较差。