The Evaluation of Comprehensive Transportation System in Inner Mongolia Based on Principal Component Analysis

2014 ◽  
Vol 505-506 ◽  
pp. 782-786
Author(s):  
Chun Mei Zhang ◽  
Zhan Xin Ma ◽  
Lu Lu Zhai ◽  
Xin Yu Cui ◽  
Xiao Biao Zhao
Keyword(s):  
Principal Component Analysis ◽  
Inner Mongolia ◽  
Rapid Development ◽  
Principal Component ◽  
Component Analysis ◽  
Transportation System ◽  
Autonomous Region ◽  
Economic Output ◽  
Transportation Development ◽  
Inner Mongolia Autonomous Region

Based on the relevant data of comprehensive transportation system in Inner Mongolia Autonomous Region from 1990 to 2011, the transport equipment, transport mileage, transport capacity, and the transport share of the total economic output in four aspects are studied. Then we select 13 indicators to build the evaluation of comprehensive transportation system in Inner Mongolia Autonomous Region. Using SPSS17.0 software to perform the principal component analysis could get the evaluation of the development of comprehensive transportation system in Inner Mongolia, which has maintained rapid development in the past 22 years, especially after 2003, higher than previous years. It is in accordance with the current transportation development of Inner Mongolia Autonomous Region, next we verify the feasibility of the Principal Component Analysis (PCA) on transportation problem. The method also has theoretical significance of research on relevant aspects of other areas.

scholarly journals Forensic analysis on printer inks via chemometrics

2021 ◽  
Vol 1192 (1) ◽  
pp. 012029
Author(s):  
L H Mohd Zawawi ◽  
N F Mohamed Azmin ◽  
M F Abd. Wahab ◽  
S I Ibrahim ◽  
M Y Mohd Yunus
Keyword(s):  
Principal Component Analysis ◽  
Digital Media ◽  
Graphical Representation ◽  
Rapid Development ◽  
Principal Component ◽  
Component Analysis ◽  
Forensic Analysis ◽  
Criminal Cases ◽  
Trial Court ◽  
Wide Range

Abstract Printer inks are becoming necessary for utilization for wide range of purposes by society in current times with rapid development in technology and digital media area. Thus, forgery and counterfeiting becoming easier for the criminals. It is dangerous as some criminals will misused the technology by mean of addition and adulteration of parts of text or numbers on document as the inks and document can be made as an evidence in the trial court. Thus, the characterization and differentiation of the printed inks in the suspected documents (civil or criminal cases) may provide important information about the authenticity of the printer inks. The focus of this study to differentiate the chemical component of three different types of sample inks by incorporation of FTIR spectrophotometer with principal component analysis. The unique features of the ink samples were unmasked from the score plots of the principal component analysis. Thus, the graphical representation provided by the FTIR spectra with principal component analysis enabled the discrimination certain chemical in the printer inks.

scholarly journals The Temporal-Spatial Distribution and Information-Diffusion-Based Risk Assessment of Forest Fires in China

2021 ◽  
Vol 13 (24) ◽  
pp. 13859
Author(s):  
Shu Wu
Keyword(s):  
Risk Assessment ◽  
Principal Component Analysis ◽  
Spatial Distribution ◽  
Forest Fire ◽  
Forest Fires ◽  
Inner Mongolia ◽  
Information Diffusion ◽  
Principal Component ◽  
Component Analysis ◽  
Expected Number

As forest fires are becoming a recurrent and severe issue in China, their temporal-spatial information and risk assessment are crucial for forest fire prevention and reduction. Based on provincial-level forest fire data during 1998–2017, this study adopts principal component analysis, clustering analysis, and the information diffusion theory to estimate the temporal-spatial distribution and risk of forest fires in China. Viewed from temporality, China’s forest fires reveal a trend of increasing first and then decreasing. Viewed from spatiality, provinces characterized by high population density and high coverage density are seriously affected, while eastern coastal provinces with strong fire management capabilities or western provinces with a low forest coverage rate are slightly affected. Through the principal component analysis, Hunan (1.33), Guizhou (0.74), Guangxi (0.51), Heilongjiang (0.48), and Zhejiang (0.46) are found to rank in the top five for the severity of forest fires. Further, Hunan (1089), Guizhou (659), and Guanxi (416) are the top three in the expected number of general forest fires, Fujian (4.70), Inner Mongolia (4.60), and Heilongjiang (3.73) are the top three in the expected number of large forest fires, and Heilongjiang (59,290), Inner Mongolia (20,665), and Hunan (5816) are the top three in the expected area of the burnt forest.

scholarly journals Principal Component Analysis as a Statistical Tool for Concrete Mix Design

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2668
Author(s):  
Janusz Kobaka
Keyword(s):  
Principal Component Analysis ◽  
Rapid Development ◽  
Principal Component ◽  
Component Analysis ◽  
Mix Design ◽  
Statistical Tool ◽  
Concrete Mix Design ◽  
Concrete Mix ◽  
2D And 3D ◽  
Economic Considerations

With the recent and rapid development of concrete technologies and the ever-increasing use of concrete, adapting concrete to the specific needs and applications of civil engineering is necessary. Due to economic considerations and care for the natural environment, improving the methods currently used in concrete design is also necessary. In this study, the author used principal component analysis as a statistical tool in the concrete mix design process. Using a combination of PCA variables and 2D and 3D factors has made it possible to refine concrete recipes. Thirty-eight concrete mixes of different aggregate grades were analyzed using this method. The applied statistical analysis showed many interesting relationships between the properties of concrete and the content of its components such as the clustering of certain properties, showing dependence between the properties and the quantities of certain ingredients in concrete, and reducing noise in the data, which most importantly simplifies interpretation. This method of analysis can be used as an aid for concrete mix design.

scholarly journals Evaluation of Water Resources Carrying Capacity Using Principal Component Analysis: An Empirical Study in Huai’an, Jiangsu, China

Water ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 2587
Author(s):  
Fan Wu ◽  
Zhicheng Zhuang ◽  
Hsin-Lung Liu ◽  
Yan-Chyuan Shiau
Keyword(s):  
Principal Component Analysis ◽  
Water Resources ◽  
Carrying Capacity ◽  
Evaluation System ◽  
Rapid Development ◽  
Supply And Demand ◽  
Principal Component ◽  
Component Analysis ◽  
Research Perspective ◽  
Water Resources Carrying Capacity

With the rapid development of urbanization, problems such as the tight supply and demand of water resources and the pollution of the water environment have become increasingly prominent, and the pressure on the carrying capacity of water resources has gradually increased. In order to better promote the sustainable development of cities, it is extremely important to coordinate the relationship between water resources and economic society. This study analyzed the current research status of water resources carrying capacity from two aspects, i.e., research perspective and research methodology, established an innovative evaluation system, and used the principal component analysis to analyze the water resources carrying capacity in Huai’an City, an important city in China’s Huaihe River Ecological Economic Zone. Based on the results, it is found that the water resources carrying capacity of Huai’an City has been declining year by year from 2013 to 2019. Based on the evaluation results, suggestions and measures to improve the water resources carrying capacity of the empirical city are proposed to provide an important decision basis for the coordinated development of urban economy, society, and water resources.

Coupling Degree Evaluation of China’s Internet Financial Ecosystem Based on Entropy Method and Principal Component Analysis

2019 ◽  
Vol 7 (5) ◽  
pp. 399-421 ◽  
Author(s):  
Rongxi Zhou ◽  
Yahui Xiong ◽  
Ning Wang ◽  
Xizu Wang
Keyword(s):  
Principal Component Analysis ◽  
Technological Innovation ◽  
Rapid Development ◽  
External Environment ◽  
Principal Component ◽  
Component Analysis ◽  
Global Perspective ◽  
Entropy Weight ◽  
Coordinated Development ◽  
Empirical Results

Abstract This paper attempts to evaluate the coordinated development state of the subsystems within the internet financial ecosystem in China from 2011 to 2016. Focusing on the main business modes, technological innovation, and the external environment, we select 29 indicators to construct an index system and adopt a coupling coordination degree model for evaluation. Furthermore, we use two weight calculation methods, entropy weight and principal component analysis, to ensure the robustness of the results. The empirical results show that China’s internet financial ecosystem experienced five development stages from 2011 to 2016, which are moderate disorder, near disorder, weak coordination, intermediate coordination, and good coordination. Different methods of obtaining weights have little effect on the empirical results. These findings suggest that at the beginning, the coordinated development of China’s internet financial ecosystem was hindered by factors including the scarcity of main business modes and the defect of technological innovation; then, with the rapid development of China’s internet industry, the external environment became another drawback in coordinated development. Finally, based on the findings, we give some policy recommendations from a global perspective to achieve a sustainable internet financial ecosystem.

Principal component analysis of fluoride geochemistry of groundwater in Shanxi and Inner Mongolia, China

2013 ◽  
Vol 135 ◽  
pp. 124-129 ◽  
Author(s):  
Shan Hu ◽  
Ting Luo ◽  
Chuanyong Jing
Keyword(s):  
Principal Component Analysis ◽  
Inner Mongolia ◽  
Principal Component ◽  
Component Analysis

scholarly journals An Improved Algorithm for Extracting Subtle Features of Radiation Source Individual Signals

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 246 ◽  
Author(s):  
Jingchao Li ◽  
Dongyuan Bi ◽  
Yulong Ying ◽  
Kai Wei ◽  
Bin Zhang
Keyword(s):  
Principal Component Analysis ◽  
Hilbert Transform ◽  
Radiation Source ◽  
Signal To Noise Ratio ◽  
Rapid Development ◽  
Recognition Rate ◽  
Principal Component ◽  
Component Analysis ◽  
Hybrid Features ◽  
Pca Algorithm

With the rapid development of communication and information technology, it is difficult for traditional signal detection and recognition methods to accurately acquire and identify the intelligence under complex environments. In order to solve this problem, this paper proposes a subtle feature extraction and recognition algorithm for radiation source individual signals based on multidimensional hybrid features. Firstly, Hilbert transform was performed on the radiation source signals from 10 identical radio devices, and the subtle features of different radiation sources’ signals were extracted. Then, traditional principal component analysis (PCA) algorithm was used to extract and reduce the principal components of the extracted feature data sets. Aiming at the insufficiency of traditional PCA algorithm, an improved principal component analysis algorithm was proposed. At last, a gray relation algorithm was used to classify and identify the radiation source individual signals, and the recognition rate was calculated. Experimental results show that Hilbert transform combined with the improved PCA algorithm can achieve a recognition rate of 99.67% for the "fingerprint" features of radiation source individual signals under the signal-to-noise ratio (SNR) of 20dB. Compared with the traditional algorithms, the recognition rate increased by 5.67%. Therefore, it provides a powerful theoretical basis for extracting subtle features of radiation source devices under complex electromagnetic environments.

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