Research on the weight of influence factors in 10kV cable network based on data analysis and information theory

2018 ◽  
Author(s):  
Jiaming Li ◽  
Jian Liu ◽  
Jiankang Zheng ◽  
Zhihua Zhang ◽  
Long Xu ◽  
...  
Keyword(s):  
Information Theory ◽  
Data Analysis ◽  
Influence Factors ◽  
Cable Network

Research on Credit Evaluation Model of C to C E-Commerce Based on Trust Influence Factors

2017 ◽  
Vol 14 (1) ◽  
pp. 189-194
Author(s):  
Xiuyan Bai
Keyword(s):  
Data Analysis ◽  
Evaluation Model ◽  
Descriptive Analysis ◽  
Influence Factors ◽  
Third Party ◽  
Trust Mechanism ◽  
The Third ◽  
Factors Influencing ◽  
Five Factors ◽  
The Third Party

Factors influencing consumer trust in C to C E-commerce were investigated through questionnaire in the Thesis and SPSS statistical software was used to conduct data analysis for questionnaire results. In data analysis, descriptive analysis, factor analysis and regression analysis were successively conducted in the Thesis and five factors influencing the trust for website and vendor by consumers were extracted in the Thesis through analysis. Finally, trust mechanism was discussed from five aspects, respectively legal restraint, market, industry supervision, the third-party certification, the third-party guarantee and trust evaluation.

Influencing Factors Study of the Contemporary Spatial Expansion of Wuhan

2013 ◽  
Vol 357-360 ◽  
pp. 1911-1917
Author(s):  
Xia Li
Keyword(s):  
Data Analysis ◽  
Urban Space ◽  
Industrial Structure ◽  
Academic Research ◽  
Influence Factors ◽  
Urban Land Use ◽  
Transitional Period ◽  
Impact Factors ◽  
Systematic Research ◽  
Spatial Expansion

The rapid urban development of Chinas city during the transitional period has received extensive academic research and policy attention. This study inquired into the process, features and impact factors of spatial expansion in Wuhan during the transitional period. This study conducted a systematic research of the transitional urban space and using data analysis to explore the spatial logic and inherent laws underlying the spatial expansion of Wuhan. Based on data analysis via SPSS, three primary components closely related to urban land use change are identified. Corresponding influence factors under the spatial expansion are explored. Economic development, urbanization level, industrial structure, the foreign investment and other indicators drive the spatial expansion of Wuhan, and it is urgent to optimize the current space framework of the downtown areas for the creation of a sustainable and effective urban space form. This study also indicates the new trends of spatial expansion and relevant recommendations for the future development of Wuhan.

scholarly journals Complex systems are always correlated but rarely information processing

2021 ◽  
Author(s):  
Karoline Wiesner ◽  
James Ladyman
Keyword(s):  
Information Theory ◽  
Information Processing ◽  
Data Analysis ◽  
Pattern Formation ◽  
Complex Systems ◽  
Symbolic Representation ◽  
Versus Data ◽  
Open Questions ◽  
First Case ◽  
Case Versus

Abstract `Complex systems are information processors' is a statement that is frequently made. Here we argue for the distinction between information processing -- in the sense of encoding and transmitting a symbolic representation -- and the formation of correlations (pattern formation / self-organisation). The study of both uses tools from information theory, but the purpose is very different in each case: explaining the mechanisms and understanding the purpose or function in the first case, versus data analysis and correlation extraction in the latter. We give examples of both and discuss some open questions. The distinction helps focus research efforts on the relevant questions in each case.

scholarly journals Analisis Faktor-Faktor Yang Berpengaruh Terhadap Kinerja Pegawai Badan Pengelolaan Keuangan Daerah Propinsi Sulawesi Selatan

Al-Buhuts ◽  
2017 ◽  
Vol 13 (2) ◽  
pp. 90-108
Author(s):  
Hasmawati Hasmawati
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Multiple Regression Analysis ◽  
Financial Management ◽  
Influence Factors ◽  
Working Environment ◽  
Dominant Factor ◽  
Management Board ◽  
Factors Analysis ◽  
Descriptive Method

 The aim of this research is to know and analysing of the influence of working motivation, working environment and working culture, towards the staffs’ performance  of financial management South celebest province and dominant factors analysis which influencing towards staffs performance. This research is caaried out at local financial management in South Celebes Province by utilizing 90 person as respondents. The data analysis used is a descriptive method by explaining the respondents chracteristics and variable description of research. Thus, the quatitave data analysis use multiple regression analysis throught the SPSS program for knowing the working motivation, working environment, working culture  as the influence factors towards the staffs’ performance whether simultanious or parcial. The result of this research shows that the simultanious whole independent varables observed positively influence the staffs’s performance of local finacial management Board in the south celebes Province. It seems that the dominant factor influence the staffs’ performabnce is the working environment. Based on the result of this research, it is recommendated to  improve the staffs’ performance of local financial management board of South celebes Province needs working motivation, working environment and working culture

scholarly journals Analysis of the Uncertainty in the relationship between Self-Determined Motivation and competitive Anxiety in dual-career students: Application of Information Theory and Bayesian Networks

2018 ◽  
Author(s):  
Xavier Ponseti ◽  
Pedro L. Almeida ◽  
Joao Lameiras ◽  
Bruno Martins ◽  
Aurelio Olmedilla-Zafra ◽  
...  
Keyword(s):  
Information Theory ◽  
Data Analysis ◽  
Intrinsic Motivation ◽  
Bayesian Networks ◽  
Dual Career ◽  
Psychological Variables ◽  
Competitive Anxiety ◽  
Psychosocial Studies ◽  
The Relationship ◽  
Probability Trees

This study is framed on the Information Theory as a constructive criterion to generate probabilistic distributions –through the elaboration of Bayesian Networks- and to reduce the uncertainty in the occurrence and relationship between two key psychological variables associated with the sports’ performance: Self-Determined Motivation and Competitive Anxiety. We analyzed 674 universitary students/athletes who competed in the 2017 Universitary Games (Universiade) in México, from 44 universities, with an average age of 21 years old (SD = 2.07), and with a sportive experience of 8.61 years of average (SD = 5.15). Methods: Regarding the data analysis, first of all a CHAID algorithm was carried out for to know the independence links among variables, and then two Bayesian networks (BN) were elaborated. The validation of the BN revealed AUC values ranging from 0.5 to 0.92. Subsequently, various instantations were carried out with hypothetical values applied to the “bottom” variables. Results showed two probability trees that have Extrinisic Motivation and Amotivation at the top, while the anxiety/activation due to the worry for performance was at the bottom of probabilities. The instantiations carried out support the existence of these probabilistic relationships, demonstrating the little influence on the competition anxiety generated by the intrinsic motivation. In conclusion, the reduction of the uncertainty made up by the restricted BN may aloe to re-introduce Information Theory principles in psychosocial studies, allowing authors to obtain useful probabilities values upon target psychological variables related with sportive performance.

Research and Analysis on Injury Factors of College Sports Based on SIIR Survey Instrument

2013 ◽  
Vol 791-793 ◽  
pp. 907-911
Author(s):  
Hai Xia Li ◽  
Rui Yun Zhang
Keyword(s):  
Data Analysis ◽  
Sports Injuries ◽  
Influence Factors ◽  
Sports Injury ◽  
Survey Instrument ◽  
College Sports ◽  
Working Capacity ◽  
Regression Procedure ◽  
Survey Instruments ◽  
The Relationship

In recent years, college is a place where sports injury is the highest and the most frequent. Therefore, it arouses a great concern in the society. In this paper, we use SIIR survey instrument to investigate part of the primary and secondary colleges in Shandong Province. We analyze the determination factors and characteristics of empirical treatment cases of the multiple sports injury. We use data analysis and processing principle of SIIR survey instrument to analyze the characteristics and causes of sports injuries. The multiple regression procedure of SIIR survey instrument is used to build the model. The model is built on the base of the relationship between the age, sex, grade of the students and the injury. We integrate the influence factors of society and college to analyze the sports injury factors. Through the scrutiny of SIIR survey instruments, we can improve the working capacity of the college to prevent sports injuries. We can also reduce the frequency of college sports injuries.

Gaussianization for Multivariate, High-dimensional Earth Observation data Analysis

2021 ◽  
Author(s):  
J. Emmanuel Johnson ◽  
Maria Piles ◽  
Valero Laparra ◽  
Gustau Camps-Valls
Keyword(s):  
Information Theory ◽  
Data Analysis ◽  
Hyperspectral Image ◽  
Generative Models ◽  
Earth Observation ◽  
Observation Data ◽  
Earth System ◽  
Multivariate Gaussian Distribution ◽  
System Data ◽  
Earth Observation Data

<p>Long-standing questions in multivariate statistics, information theory and machine learning reduce to estimating multivariate densities. However, this is still an unresolved problem and one of the biggest challenge in general, and for Earth system data analysis in particular, due to the high dimensionality (spatial, temporal and/or spectral) of the data streams. Gaussianization is a class of generative models (normalizing flows) that is effective in computing density estimates by using  a sequence of composite invertible transformations which transform data from its original domain to a multivariate Gaussian distribution. The methodology in turn allows us to estimate information theory measures (ITMs), which are relevant for the analysis and characterization of Earth system data superseding the mean, variance and correlation, as higher order measures, thereby capturing more complexity and providing more insight into various problems. We show that our Rotation-Based Iterative Gaussianization (RBIG) method allows us to compute ITMs from multivariate (spatio-spectral-temporal) Earth data efficiently in both computation and memory terms, directly from the Gaussianizing transformation, while being robust to data dimensionality . We demonstrate how Gaussianization is useful in various Earth observation data analysis problems, from hyperspectral image analysis to drought detection in data cubes.</p>

Dealing with categorical missing data using CleanerR

2019 ◽  
Author(s):  
Rafael Pereira ◽  
Fabio Porto
Keyword(s):  
Information Theory ◽  
Data Analysis ◽  
Missing Data ◽  
Data Integration ◽  
Missing Values ◽  
Data Input ◽  
Functional Dependencies ◽  
The World ◽  
Account Information

Missing data is a common problem in the world of data analysis. They appear in datasets due to a multitude of reasons, from data integration to poor data input. When faced with the problem, the analyst must decide what to do with the missing data since its not always advisable to discard these values from your analysis. On this paper we shall discuss a method that takes into account information theory and functional dependencies to best imput missing values.

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