scholarly journals Modulus of Elasticity for Grain-Supported Carbonates—Determination and Estimation for Preliminary Engineering Purposes

2021 ◽  
Vol 11 (13) ◽  
pp. 6148
Author(s):  
Zlatko Briševac ◽  
Davor Pollak ◽  
Ana Maričić ◽  
Andreja Vlahek
Keyword(s):  
Modulus Of Elasticity ◽  
Model Development ◽  
Regression Tree ◽  
Physical And Mechanical Properties ◽  
Elastic Behaviour ◽  
Tree Model ◽  
Tree Models ◽  
Complex Models ◽  
Regression Tree Model ◽  
Simple Regression

The determination and estimation of elastic behaviour are essential in engineering practise, especially in quarrying, mining, construction, and all engineering professions that perform operations dealing with rock materials. Young’s modulus, or modulus of elasticity, is the most important property describing the deformability of rock material. In this paper, grain-supported carbonates from Croatia are described and their elastic modulus and significant physical and mechanical properties are determined. The analysis of the collected data was performed in the R statistical environment. Estimation models based on multiple linear regression and the regression tree model were created. The methodology of model development and evaluation in R environment is described in detail. According to the more stringent coefficients (RMSECV and adjusted R2) used to evaluate the success of the estimation, simple regression tree models were found to perform well for the preliminary estimation, while more complex models based on Bagging performed very well.

scholarly journals Regression Tree Model for Predicting Game Scores for the Golden State Warriors in the National Basketball Association

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 835 ◽  
Author(s):  
Mei-Ling Huang ◽  
Yi-Jung Lin
Keyword(s):  
Regression Models ◽  
Predictive Accuracy ◽  
Regression Tree ◽  
National Basketball Association ◽  
Sporting Events ◽  
Linear Regression Models ◽  
Tree Model ◽  
Weak Symmetry ◽  
Tree Models ◽  
Regression Tree Model

Data mining is becoming increasingly used in sports. Sport data analyses help fans to understand games and teams’ results. Information provided by such analyses is useful for game lovers. Specifically, the information can help fans to predict which team will win a game. Many scholars have devoted attention to predicting the results of various sporting events. In addition to predicting wins and losses, scholars have explored team scores. Most studies on score prediction have used linear regression models to predict the scores of ball games; nevertheless, studies have yet to use regression tree models to predict basketball scores. Therefore, the present study analyzed game data of the Golden State Warriors and their opponents in the 2017–2018 season of the National Basketball Association (NBA). Strong and weak symmetry requirements were identified for each team. We developed a regression tree model for score prediction. After predicting the scores of each player on two teams, we summed and compared the predicted total scores to obtain the predicted results (lose or win) of the team of interest. The results of this study revealed that the regression tree model can effectively predict the score of each player and the total score of the team. The model achieved a predictive accuracy of 87.5%.

scholarly journals A global bibliometric perspective on soil erosion modelling

2020 ◽  
Author(s):  
Nejc Bezak ◽  
Keyword(s):  
Conference Proceedings ◽  
Soil Erosion ◽  
Regression Tree ◽  
Tree Model ◽  
Boosted Regression Tree ◽  
Field Activity ◽  
Erosion Modelling ◽  
Meta Information ◽  
Number Of Citations ◽  
Regression Tree Model

<p>Systematic bibliometric investigations are useful to evaluate and compare the scientific impact of journal papers, book chapters and conference proceedings. Such studies allow the detection of emerging research topics, the analyses of cooperation networks, and the collection of in-depth insights into a specific research topic. In the presented work, we carried out a bibliometric study in order to obtain an in-depth knowledge on soil erosion modelling applications worldwide.</p><p>As a starting point, we used the soil erosion modelling meta-analysis data collection generated by the authors of this abstract in a joint community effort. This database contains meta-information of more than 3,000 documents published between 1994 and 2018 that are indexed in the SCOPUS database. The documents were reviewed and database entries verified. The database contains various types of meta-information about the modelling studies (e.g., model used, study area, input data, calibration, etc.). The bibliometric information was also included in the database (e.g., number of citations, type of publication, Scopus category, etc.). We investigated differences among publication types and differences between papers published in journals that are part of various Scopus categories. Moreover, relationships between publication CiteScore, number of authors, and number of citations were analyzed. A boosted regression tree model was used to detect the relative impact of the selected meta-information such as erosion model used, spatial modelling scale, study period, field activity on the total number of citations. Detailed investigation of the most cited papers was also conducted. The VOSviewer software was used to analyze citations, co-citations, bibliographic coupling, and co-authorship networks of the database entries.  </p><p>Our bibliometric investigations demonstrated that journal publications, on average, receive more citations than book series or conference proceedings. There were differences among the erosion models used, and some specific models such as the WaTEM/SEDEM model, on average, receive more citations than other models (e.g., USLE). It should also be noted that self-citation rates in case of most frequently used models were similar. Global studies, on average, receive more citations than studies dealing with plot, regional, or national scales. According to the boosted regression tree model, model calibration, validation, or field activity do not have significant impact on the obtained publication citations. Co-citation investigation revealed some interesting patterns. Our results also indicate that papers about soil erosion modeling also attract citations from different fields and better international cooperation is needed to advance this field of research with regard to its visibility and impact on human societies.    </p>

scholarly journals A Dynamic Adjustment Model of Cruising Taxicab Fleet Size Combined the Operating and Flied Survey Data

2020 ◽  
Vol 12 (7) ◽  
pp. 2776 ◽  
Author(s):  
Xiaofei Ye ◽  
Min Li ◽  
Zhongzhen Yang ◽  
Xingchen Yan ◽  
Jun Chen
Keyword(s):  
Waiting Time ◽  
Layer Structure ◽  
Operating Time ◽  
Regression Tree ◽  
Threshold Value ◽  
Dynamic Adjustment ◽  
Tree Model ◽  
Fleet Size ◽  
Average Waiting Time ◽  
Regression Tree Model

Due to the lack of adjustment index systems for taxi fleet sizes in China, this paper used the taxi operating datasets from Ningbo City and established a regression tree model to consider the endogenous indicators that affect taxi fleet sizes. Then, a dynamic adjustment mechanism of taxi fleet sizes was proposed by combining the exogenous and endogenous indicators. The importance of the exogenous and endogenous indicators was sorted using the Delphi method. The threshold value of each indicator was also given. The results indicated that (1) in the three-layer structure of the regression tree model, the mileage utilization had the strongest effect on the fleet size of taxis, and the F statistic was 63.73; followed by the average daily revenue of a single taxi, the average waiting time to catch a single taxi, the average operating time of a single taxi, and the revenue per 100 km. The overall accuracy of the model was found to be valid. (2) When the mileage utilization was less than 0.6179 and the average daily revenue of a single taxi was less than 798.38 Yuan, the fleet size of cruising taxis was surplus and should be reduced by 362 vehicles. (3) When the mileage utilization was more than 0.6774 and the average waiting time to catch a single taxi was more than 259.09 s, the fleet size of cruising taxis was insufficient, and we suggest an increase of 463 taxis.

scholarly journals Research on the Relationship Between Teachers’ Professional Skills and Students’ Expectations for Improving the Study Environment

2018 ◽  
Vol 4 (8) ◽  
pp. 109
Author(s):  
Aida Stikliene
Keyword(s):  
Regression Tree ◽  
Point Of View ◽  
Learning Problems ◽  
Data Collection Tool ◽  
Tree Model ◽  
Professional Skills ◽  
Working Students ◽  
Variate Analysis ◽  
The Relationship ◽  
Regression Tree Model

The teacher's attitude towards the teaching process and communication skills is of particular importance and plays a crucial role in today’s rapidly changing world. It has to go together, raising consciousness and awareness of individuals on study environment issues and ensuring that they contribute to solutions of learning problems. The research was conducted with 405 prospective professionals from the Faculty of Forest Sciences and Ecology, Aleksandras Stulginskis University. An interactive questionnaire ‘Study subject in student’s eyes’ (SSSE) developed at Aleksandras Stulginskis University (2014–2017) was used as the data collection tool. This article analyses the teachers’ pedagogical work from the students’ point of view. The multi-variate analysis and regression tree model were used in the interpretation of results. The results confirmed the hypothesis that hard working students better evaluate teachers’ professional skills. It seems that elder course students with age have higher expectations from the teaching environment. Keywords:

Sign in / Sign up

Export Citation Format

Share Document