An Empirical Analysis on the Level of New Industrialization in Hefei

2011 ◽  
Vol 361-363 ◽  
pp. 1790-1794
Author(s):  
Zheng Qing Luo ◽  
Jun Yan Luo
Keyword(s):  
Principal Component Analysis ◽  
Empirical Analysis ◽  
Quantitative Study ◽  
Rapid Development ◽  
Principal Component ◽  
Intermediate Stage ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Medium Term ◽  
New Industrialization

Hefei is in a period of rapid development of new industrialization, but there is no quantitative study on where the new industrialization level is. Therefore, this article designs a set of evaluation index system of new industrialization, and uses principal component analysis to calculate the new Industrialization level in Hefei. The result shows that Hefei has been in the medium-term of the intermediate stage of new industrialization.

Research on the Sustainable Development Based on PREES Model of Beijing

2013 ◽  
Vol 291-294 ◽  
pp. 1605-1609
Author(s):  
Wen Yan Guo ◽  
Li Ma ◽  
Qiong Wang ◽  
Xiao Liu Shen
Keyword(s):  
Principal Component Analysis ◽  
Sustainable Development ◽  
Empirical Analysis ◽  
Evaluation System ◽  
Rapid Development ◽  
Principal Component ◽  
Coordinated Development ◽  
The Sustainable Development ◽  
The City ◽  
Coordination Degree

This paper studies the coordinated development of Beijing's population, resources, environment, economic and society. With the rapid development of the city, Beijing’s population, society and economic is getting more and more contradictive against its resources and environment, under which circumstance a scientific study on the coordinated development is urgently required. This essay is based on the data of last 10 years of Beijing, and formulates a PREES model of the PREES model in Beijing. This study uses the method of principal component analysis via SPSS, establishes the coordination degree evaluation system of Beijing’s population, resources, environment, economic and society, and runs an empirical analysis afterward. This essay calculates the coordination degree of Beijing’s population, resources, environment, economic and society, analyzes and studies the main issues in Beijing’s coordinated development, and gives relative suggestions.

Effect Evaluation of Video Surveillance System on the Basis of Principal Component Analysis

2015 ◽  
Vol 713-715 ◽  
pp. 479-481
Author(s):  
Tao Zhu ◽  
Wei Jun Hong
Keyword(s):  
Principal Component Analysis ◽  
Video Surveillance ◽  
Index System ◽  
Surveillance System ◽  
Principal Component ◽  
Component Analysis ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Video Surveillance System ◽  
Effect Evaluation

The effect evaluation of video surveillance system is important for the effect of expected protection on the system. A comprehensive effect evaluation index system of video surveillance system is established. The Principal Component Analysis (PCA) method is applied on the established index system to obtain a new evaluation index system. It is proved in instances that the effect evaluation method of video surveillance system with the application of the index system is capable of evaluating the video surveillance system effectively and quantitatively. The protective effect of the video surveillance system is evaluated objectively on the basis of the new index system with the PCA.

The Forecasts Study of City Economy and Cyclic Integrating Development

2013 ◽  
Vol 798-799 ◽  
pp. 1144-1147
Author(s):  
Tian Shui Lin
Keyword(s):  
Principal Component Analysis ◽  
Quantitative Evaluation ◽  
Circular Economy ◽  
Arima Model ◽  
Principal Component ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Chongqing City ◽  
Economic Trends ◽  
Comprehensive Study

In this paper, we select the multi-dimensional evaluation index system based on principal component analysis for quantitative evaluation of circular economy in Chongqing . We use ARIMA model to predict Chongqing city cycle economic trends which rely on a comprehensive study in the development of circular economy status quote.

scholarly journals Constructing a Method for an Evaluation Index System Based on Graph Distance Classification and Principal Component Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Keyou Shi ◽  
Yong Liu ◽  
Zhijun Zhang ◽  
Qing Yu ◽  
Qiucai Zhang
Keyword(s):  
Principal Component Analysis ◽  
Environmental Quality ◽  
Index System ◽  
Principal Component ◽  
Component Analysis ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Radiation Environment ◽  
Graph Distance ◽  
System A

Based on the importance of having an evaluation index system, a new method that combines PCA with graph distance classification is presented to make up the deficiencies of principal component analysis in the process of index screening, and this method is applied in the construction of an evaluation index system for the environmental quality of decommissioning uranium tailing. The seepage indexes were classified into six classes using graph distance classification, which selects the representative elements, including pH, ∑α, 210Pb, 210Po, F−, and NO3−. All of the representative elements were analyzed by PCA while determining the seepage indexes, including pH, U, Ra, ∑α, NH4-N, and F−, and establishing an index system for environmental quality evaluation that consists of two primary indexes (seepage and radiation environment) and 12 secondary indexes. The results showed that the model had ensured that the sifted indexes had a significant effect on the evaluation result and avoided the deletion of some important indexes and that it had stronger applicability and maneuverability.

The Competitiveness of Ecological Civilization

2011 ◽  
Vol 356-360 ◽  
pp. 2620-2623
Author(s):  
Yi Xia Tao ◽  
Xue Hua Zhang
Keyword(s):  
Principal Component Analysis ◽  
Index System ◽  
Comprehensive Evaluation ◽  
Principal Component ◽  
Component Analysis ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Ecological Civilization ◽  
Independent Components ◽  
Autonomous Regions

Abstract. According to the meaning of ecological civilization, we build an evaluation index system of ecological civilization competitiveness. We select 30 provinces or autonomous regions in China, collect the relevant data and through principal component analysis 9 independent components are picked up from 19 comprehensive evaluation indices which reflect the competitiveness of ecological civilization. Then we evaluate and rank the regions’ ecological civilization competitiveness. By comparing the results, we find out strengths and gaps of the regions as well as the related reasons.

Research on Supply and Demand of Xi'an Real Estate Market

2011 ◽  
Vol 368-373 ◽  
pp. 3078-3082
Author(s):  
Zhou Ji Meng ◽  
Tao Zhou ◽  
Shu Hua Gao
Keyword(s):  
Principal Component Analysis ◽  
Spectral Analysis ◽  
Real Estate ◽  
Spectral Density ◽  
Supply And Demand ◽  
Principal Component ◽  
Real Estate Market ◽  
Medium Term ◽  
Real Estate Price ◽  
Synthetic Indicators

In the passage, the indicators of supply and demand of real estate market in Xi'an are established, and such indicators are synthesized into a class of synthetic indicators using “principal component analysis”. After the spectral analysis of synthetic indicators, periodic change of supply and demand of real estate through spectral density could be determined. Through the analysis, great randomness existed in supply and demand of real estate in Xi’an. Furthermore, in the medium term, a 3.3 years’ secondary cycle still existed in synthetic indicators of demand, while randomness existed in synthetic indicators of supply. Such findings suggest a declined trend existed in real estate price in medium term of Xi’an.

scholarly journals Optimal Vehicle Pose Estimation Network Based on Time Series and Spatial Tightness with 3D LiDARs

2021 ◽  
Vol 13 (20) ◽  
pp. 4123
Author(s):  
Hanqi Wang ◽  
Zhiling Wang ◽  
Linglong Lin ◽  
Fengyu Xu ◽  
Jie Yu ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Time Series ◽  
Pose Estimation ◽  
Point Cloud ◽  
Principal Component ◽  
Component Analysis ◽  
Evaluation Index ◽  
Evaluation Indexes ◽  
Learning Network ◽  
Estimation Algorithms

Vehicle pose estimation is essential in autonomous vehicle (AV) perception technology. However, due to the different density distributions of the point cloud, it is challenging to achieve sensitive direction extraction based on 3D LiDAR by using the existing pose estimation methods. In this paper, an optimal vehicle pose estimation network based on time series and spatial tightness (TS-OVPE) is proposed. This network uses five pose estimation algorithms proposed as candidate solutions to select each obstacle vehicle's optimal pose estimation result. Among these pose estimation algorithms, we first propose the Basic Line algorithm, which uses the road direction as the prior knowledge. Secondly, we propose improving principal component analysis based on point cloud distribution to conduct rotating principal component analysis (RPCA) and diagonal principal component analysis (DPCA) algorithms. Finally, we propose two global algorithms independent of the prior direction. We provided four evaluation indexes to transform each algorithm into a unified dimension. These evaluation indexes’ results were input into the ensemble learning network to obtain the optimal pose estimation results from the five proposed algorithms. The spatial dimension evaluation indexes reflected the tightness of the bounding box and the time dimension evaluation index reflected the coherence of the direction estimation. Since the network was indirectly trained through the evaluation index, it could be directly used on untrained LiDAR and showed a good pose estimation performance. Our approach was verified on the SemanticKITTI dataset and our urban environment dataset. Compared with the two mainstream algorithms, the polygon intersection over union (P-IoU) average increased by about 5.25% and 9.67%, the average heading error decreased by about 29.49% and 44.11%, and the average speed direction error decreased by about 3.85% and 46.70%. The experiment results showed that the ensemble learning network could effectively select the optimal pose estimation from the five abovementioned algorithms, making pose estimation more accurate.

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.

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