scholarly journals Exploratory Data Analytics to Study the Impact of Parameters to Enhance the Population of House Sparrow (Passer Domesticus).

2021 ◽  
Author(s):  
Renukadevi. K ◽  
Merlynna Esther Maxmellion. P ◽  
Pitchumani Angayarkanni. S ◽  
Priyatharsini Rajendran
Keyword(s):  
Principal Component Analysis ◽  
House Sparrow ◽  
Passer Domesticus ◽  
Principal Component ◽  
Specific Area ◽  
Component Analysis ◽  
Adaptation Strategy ◽  
Suitable Habitat ◽  
Kendall Correlation ◽  
The Impact

Abstract To achieve a sustainable conservation or adaptation strategy, it is necessary to understand the impacts of habitat and weather on particular species. Hence the study was focused to analyze the parameters that influence the population of house sparrow in various locations of Madurai Dist. Furthermore, its present and future suitable habitats have been predicted using computational tools. Statistical analysis and correlation were performed with data gathered through random sampling. Using correlation analysis, the association between various parameters was studied. Hierarchical clustering of data was performed by a Kendall Correlation coefficient to identify the suitable habitat and weather. Subsequently the Selection of the major parameters of a study was determined using Principal Component Analysis approach. The study highlights the significance of utilizing data mining and computational analysis to precisely understand the influence of various geographical parameters on the distribution and survival of the house sparrow population in an area. Based on the results obtained, abundance and distribution of house sparrow were closely related to the area of habitat in which house sparrows were found. The preference of particular habitat can be briefly explained using Kendall Correlation Matrix and cluster analysis. Using the Principal Component Analysis (PCA) technique, the population density of the house sparrow was studied. Taking these computational analyses into account will provide a new perspective on predicting the species distribution in the specific area thereby conserving it.

Evaluation of the Aging Behavior of High Density Polyethylene in Thermal Oxidative Environment by Principal Component Analysis

2017 ◽  
Vol 727 ◽  
pp. 447-449 ◽  
Author(s):  
Jun Dai ◽  
Hua Yan ◽  
Jian Jian Yang ◽  
Jun Jun Guo
Keyword(s):  
Principal Component Analysis ◽  
Impact Strength ◽  
High Density Polyethylene ◽  
Tensile Modulus ◽  
Principal Component ◽  
Component Analysis ◽  
High Density ◽  
Aging Behavior ◽  
Data Set ◽  
The Impact

To evaluate the aging behavior of high density polyethylene (HDPE) under an artificial accelerated environment, principal component analysis (PCA) was used to establish a non-dimensional expression Z from a data set of multiple degradation parameters of HDPE. In this study, HDPE samples were exposed to the accelerated thermal oxidative environment for different time intervals up to 64 days. The results showed that the combined evaluating parameter Z was characterized by three-stage changes. The combined evaluating parameter Z increased quickly in the first 16 days of exposure and then leveled off. After 40 days, it began to increase again. Among the 10 degradation parameters, branching degree, carbonyl index and hydroxyl index are strongly associated. The tensile modulus is highly correlated with the impact strength. The tensile strength, tensile modulus and impact strength are negatively correlated with the crystallinity.

The Comprehensive Evaluation on Financial Performance of the Ceramic Company Based on Principal Component Analysis

2012 ◽  
Vol 512-515 ◽  
pp. 1098-1102 ◽  
Author(s):  
Bao Cheng He ◽  
Hong Tao Jiang
Keyword(s):  
Principal Component Analysis ◽  
Financial Performance ◽  
Performance Indicator ◽  
Comprehensive Evaluation ◽  
Principal Component ◽  
Component Analysis ◽  
Indicator System ◽  
Financial Report ◽  
Components Method ◽  
The Impact

The ceramic company financial performance indicator has multilayers, many dimensions and intersect characters, and the comprehensive evaluation on it is a big challenge. Firstly, this paper introduces principal component analysis theory and tool. Secondly, it constructs the four-dimensional evaluating indicator system based on “debt-paying ability, operation capability, profitability, and development capability”. In the end, based on the financial report data, this paper conducts an empirical principal component analysis on 20 typical ceramic enterprises’ financial performance. The conclusion is that the ceramic business finance performance is mainly decided by four greatest factors including “debt-paying ability, profitability, efficiency, development” and the impact of the four greatest factors upon the finance performance degree is different. This research’s innovation lies in using the principal components method to give the weight to the evaluating indicators objectively, providing not only the new tool for the ceramic enterprise financial performance assessment method’s evolution, but also the new mentality for the ceramic enterprise financial performance’s improvement.

scholarly journals Principal Component Analysis in the Nonlinear Dynamics of Beams: Purification of the Signal from Noise Induced by the Nonlinearity of Beam Vibrations

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
A. V. Krysko ◽  
Jan Awrejcewicz ◽  
Irina V. Papkova ◽  
Olga Szymanowska ◽  
V. A. Krysko
Keyword(s):  
Nonlinear Dynamics ◽  
Principal Component Analysis ◽  
Differential Equations ◽  
Geometric Nonlinearity ◽  
Nonlinear Differential Equations ◽  
Principal Component ◽  
Component Analysis ◽  
Harmonic Load ◽  
Linear And Nonlinear ◽  
The Impact

The paper discusses the impact of the von Kármán type geometric nonlinearity introduced to a mathematical model of beam vibrations on the amplitude-frequency characteristics of the signal for the proposed mathematical models of beam vibrations. An attempt is made to separate vibrations of continuous mechanical systems subjected to a harmonic load from noise induced by the nonlinearity of the system by employing the principal component analysis (PCA). Straight beams lying on Winkler foundations are analysed. Differential equations are obtained based on the Bernoulli-Euler, Timoshenko, and Sheremetev-Pelekh-Levinson-Reddy hypotheses. Solutions to linear and nonlinear differential equations are found using the principal component analysis (PCA).

The Principal Component Analysis of Coastal Areas

2014 ◽  
Vol 513-517 ◽  
pp. 3703-3706
Author(s):  
Qiu Ju Wang ◽  
Da Shen Xue
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Coastal Areas ◽  
Principal Component Analysis Analysis ◽  
Consumer Prices ◽  
The Government ◽  
Main Component ◽  
The Impact

In order to development the economic of China's coastal areas better, the paper mainly discusses the coastal areas of China's consumer price factors, the main use of software SPSS, using statistical analysis, principal component analysis, analysis that the impact is the main component of consumer prices and reached the level of consumer prices in coastal areas, which is conducive to the Government to take appropriate measures to faster and better development of the region's economy.

scholarly journals THE IMPACT OF REAL ESTATE INVESTMENTS ON THE PERFORMANCE OF THE ENTITIES LISTED AT THE BVB

2021 ◽  
Vol 30 (30 (1)) ◽  
pp. 177-186
Author(s):  
Silviu Cornel Virgil Chiriac
Keyword(s):  
Principal Component Analysis ◽  
Real Estate ◽  
Financial Performance ◽  
Descriptive Analysis ◽  
Composite Index ◽  
Principal Component ◽  
Component Analysis ◽  
Multidimensional Data ◽  
Data Set ◽  
The Impact

The current paper is part of a wider study which aims at identifying the determining factors of the performances of the entities in the real estate field and the setting up of a composite index of the companies’ performances based on a sample of 29 companies listed at the BVB Bucharest (Bucharest Stock Exchange) in the year 2019 using one of the multidimensional data analysis techniques, the principal component analysis. The descriptive analysis, the principal component analysis for setting up the composite index of the companies performances were applied within the study in order to highlight the most important companies from the point of view of the financial performance. The descriptive analysis of the data set highlights the overview within the companies selected for analysis. The study aims at building a synthetic indicator that will show the financial performance of the companies selected based on 9 financial indicators using the principal component analysis PCA. The 9 indicators considered for the analysis were selected based on specialised articles and they are: ROA – return on assets, which reflect the company’s capacity of using its assets productively, ROE – return on equity, which measures the efficiency of use of the stockholders’ capitals, rotation of total assets, general liquidity ratio, general solvency ratio, general dent-to-equity level, net profit margin, gross return of portfolio.

scholarly journals APPLICATION OF PRINCIPAL COMPONENT ANALYSIS TO DROUGHT INDICATORS OF THREE REPRESENTATIVE CROATIAN REGIONS

2021 ◽  
Vol 12 (22) ◽  
pp. 41-55
Author(s):  
Lidija Tadić ◽  
◽  
Tamara Brleković ◽  
Kristina Potočki ◽  
Marija Leko-Kos ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Air Temperature ◽  
Principal Component ◽  
Component Analysis ◽  
Homogeneity Test ◽  
Temperature And Precipitation ◽  
Standard Normal Homogeneity Test ◽  
Seasonal Basis ◽  
The Impact ◽  
Drought Occurrence

Drought has become a very frequent hydrological event globally, including in Croatia. It can generally be explained by air temperature and precipitation changes on an annual and seasonal basis, owing to climate change. To contribute to the knowledge on drought phenomena in Croatia, the changes in air temperature and precipitation over a relatively long period between 1951 and 2018 were analyzed. The meteorological stations included in the research were Osijek, Zagreb, and Split, which represented the climate of the entire country. Drought was estimated using the standardized precipitation evapotranspiration index, which is one of the most comprehensive drought indices. Furthermore, the drought severity and duration were calculated using run theory. These parameters were tested for homogeneity using the standard normal homogeneity test. Only the air temperature exhibited inhomogeneity, with a break year in 1991 (Zagreb and Split) and 1998 (Osijek). The existence of significant temporal trends was tested using the non-parametric Mann–Kendall trend test. The probability of drought occurrence with a certain duration and severity was calculated using the copula function. Finally, principal component analysis was applied to the computed standardized Mann–Kendall test statistic (ZMK ) to define the relevance of each parameter change and their combination in drought occurrence on a seasonal basis. Drought occurrence was less recognizable from 1951 to 1991 (1998). In the second sub-period, the impact of an increasing air temperature was the most significant variable, particularly in Zagreb.

The Correction Model of Webster Method for Intersection Delay

2011 ◽  
Vol 97-98 ◽  
pp. 503-506
Author(s):  
Han Bai ◽  
Kai Deng ◽  
Nan Wang ◽  
Qiang Qiang Qiao
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Traffic Control ◽  
Principal Component ◽  
Component Analysis ◽  
Impact Factors ◽  
Important Indicator ◽  
Correction Model ◽  
The Impact

Intersection delay, an important indicator of traffic control, is often calculated by the Webster formula nowadays. This study investigated and analyzed the delay of several intersections in Jinan using the principal component analysis to identify the impact factors of the delay. Statistical analysis was used by MATLAB to build the correction model of Webster formula for intersection delay.

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