scholarly journals Assessment of Groundwater Quality Based on Matter Element Extension Model

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Jin Jing ◽  
Qian Hui ◽  
Chen Yu-Fei ◽  
Xi Wen-Juan
Keyword(s):  
Principal Component Analysis ◽  
Drinking Water ◽  
Groundwater Quality ◽  
Principal Component ◽  
Analysis Method ◽  
Entropy Weight ◽  
Extension Method ◽  
Groundwater Quality Assessment ◽  
Extension Model ◽  
Dissolution And Precipitation

The basic theory and calculating processes of matter element extension method are discussed in detail. Mass balance simulation is used to study the changes of groundwater chemistry. Results show that calcite and dolomite are oversaturated, while gypsum, fluorite, and halite are unsaturated in the simulation path; so calcite precipitates, while gypsum, fluorite, halite, and dolomite dissolve. The changing tendency of Ca2+/Na+is apparent. Because of the dissolution and precipitation of minerals, the content of each ion changes. Parameters of groundwater are basically within the permissible limits and meet the requirement of drinking water standards. By comparing the evaluation results obtained from matter element extension method, osculating value method based on entropy weight, and principal component analysis method, it is proved that matter element extension is an effective and reasonable method for groundwater quality assessment. The converting tendency of groundwater quality is judged based on the extension indexes; this characteristic is unique of matter element extension method.

scholarly journals Groundwater Quality Assessment: An Improved Approach to K-Means Clustering, Principal Component Analysis and Spatial Analysis: A Case Study

Water ◽  
2018 ◽  
Vol 10 (4) ◽  
pp. 437 ◽  
Author(s):  
Ana Marín Celestino ◽  
Diego Martínez Cruz ◽  
Elena Otazo Sánchez ◽  
Francisco Gavi Reyes ◽  
David Vásquez Soto
Keyword(s):  
Principal Component Analysis ◽  
Spatial Analysis ◽  
Groundwater Quality ◽  
Quality Assessment ◽  
Principal Component ◽  
Component Analysis ◽  
Groundwater Quality Assessment

scholarly journals Application of Set Pair Analysis Method Based on Entropy Weight in Groundwater Quality Assessment -A Case Study in Dongsheng City, Northwest China

2011 ◽  
Vol 8 (2) ◽  
pp. 851-858 ◽  
Author(s):  
Li Pei-Yue ◽  
Qian Hui ◽  
Wu Jian-Hua
Keyword(s):  
Water Quality ◽  
Groundwater Quality ◽  
Quality Assessment ◽  
Assessment Model ◽  
Set Pair Analysis ◽  
Analysis Method ◽  
Entropy Weight ◽  
Groundwater Quality Assessment ◽  
Pair Analysis

Groundwater quality assessment is an essential study which plays important roles in the rational development and utilization of groundwater. Groundwater quality greatly influences the health of local people. However, most traditional water quality comprehensive assessment methods which have complicated formulas are difficult to apply in water quality assessment. In this paper, a novel method for groundwater quality assessment called set pair analysis was introduced and entropy weight was assigned to each index to improve the assessment model. The calculation steps are depicted in the paper and take groundwater quality assessment in Dongsheng City as a case study. The assessment results indicated that groundwater qualities in the study area were relatively good, Set Pair Analysis method, which was an optimal method for groundwater quality assessment and worth promoting, was easy to use and calculation processes which use almost all the relative information were simple, results were reasonable, reliable and intuitive.

Study on the Effect Factors of Non-Perormance Loan Ratio of Chinese Commerical Banks

2011 ◽  
Vol 50-51 ◽  
pp. 728-732
Author(s):  
Ping Li ◽  
Ming Ying Zhuo ◽  
Li Chao Feng ◽  
Rui Zhang
Keyword(s):  
Principal Component Analysis ◽  
Commercial Banks ◽  
Principal Component ◽  
Component Analysis ◽  
Analysis Method ◽  
Analysis Model ◽  
Principal Component Analysis Model ◽  
Effect Factors ◽  
Financial Indicator ◽  
Commerical Banks

Non-performance loan ratio is one of the important assessment criteria of the security of credit assets. It is also an important financial indicator to evaluate the general strength of commercial banks. Using principal component analysis method and statistical software SPSS16.0 and based on the non-performance loan ratio and relative data of some commercial banks in China in 2007, this paper provided a principal component analysis model for the non-performance loan ratio of China’s commercial banks. The factors that affect the non-performance loan ratio were refined in this paper. Finally, the characteristics of effect factors of each bank were analyzed and compared in detail.

scholarly journals Application of Principal Component Analysis Method to Determine Prediction Indexes Sensibility Sequence

2011 ◽  
Vol 26 ◽  
pp. 1346-1351
Author(s):  
Yang Guo-liang ◽  
Wang Can-zhao ◽  
Wu Shi-yue ◽  
Jia Li-qing ◽  
Zhang Sheng-zhu
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Analysis Method ◽  
Principal Component Analysis Method

Principal Component Analysis of Hydrological Data

2010 ◽  
pp. 364-388
Author(s):  
Petr Praus
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Drinking Water ◽  
Ground Water ◽  
Principal Component ◽  
Component Analysis ◽  
Data Sets ◽  
Hydrological Data ◽  
First Case

In this chapter the principals and applications of principal component analysis (PCA) applied on hydrological data are presented. Four case studies showed the possibility of PCA to obtain information about wastewater treatment process, drinking water quality in a city network and to find similarities in the data sets of ground water quality results and water-related images. In the first case study, the composition of raw and cleaned wastewater was characterised and its temporal changes were displayed. In the second case study, drinking water samples were divided into clusters in consistency with their sampling localities. In the case study III, the similar samples of ground water were recognised by the calculation of cosine similarity, the Euclidean and Manhattan distances. In the case study IV, 32 water-related images were transformed into a large image matrix whose dimensionality was reduced by PCA. The images were clustered using the PCA scatter plots.

Chemical Structure-Odor Correlation in a Series of Synthetic n-Nonen-1-ols

1995 ◽  
Vol 50 (11-12) ◽  
pp. 757-765 ◽  
Author(s):  
Yasunobu Sakoda ◽  
Kenji Matsui ◽  
Tadahiko Kajiwara ◽  
Akikazu Hatanaka
Keyword(s):  
Principal Component Analysis ◽  
Double Bond ◽  
Spatial Structure ◽  
Chemical Structure ◽  
Principal Component ◽  
Component Analysis ◽  
Acetylenic Compound ◽  
Analysis Method ◽  
Entire Series ◽  
Novel Method

In order to elucidate chemical structure-odor correlation in the all isomers of n-nonen-1- ols, an entire series of these alcohols were synthesized stereo-selectively in high purity. For unequivocal syntheses of them, geometrically selective hydrogenation of the respective acetylenic compound was adopted. The synthesized alcohols were converted to their 3,5-dinitrobenzoate derivatives with 3,5-dinitrobenzoyl chloride, and then purified by repeated recrystallization. Chemical structure-odor correlations in all the isomers of n-nonen-1-ols were elucidated by introducing a novel method to evaluate odor characteristics and by treating the obtained data statistically with the principal component analysis method (Cramer et al., 1988). The odor profiles of the tested compounds were attributable largely to the positions of the carbon- double bond. The geometries of compounds had only a little effect. With the principal component analysis, the odor profiles of the series of compounds were successfully integrated into the first and the second principal components. The first component (PC-1) consisted of combined characteristics of fruity, fresh, sweet, herbal and oily-fatty, in which herbal and oily-fatty were conversely correlated each other to the position of double-bond of the tested compounds. Of these, only (6Z)-nonen-1-ol deviated markedly from the correlation, indicative of some special interaction between the spatial structure of this compound and the sensory machinery of human.

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