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Full-Text Articles in Engineering
Application Of A Decision Tree Method With A Spatiotemporal Object Database For Pavement Maintenance And Management, Chien-Ta Chen, Chia-Tse Hung, Jyh-Dong Lin, Po-Hsun Sung
Application Of A Decision Tree Method With A Spatiotemporal Object Database For Pavement Maintenance And Management, Chien-Ta Chen, Chia-Tse Hung, Jyh-Dong Lin, Po-Hsun Sung
Journal of Marine Science and Technology
In recent years, pavement engineering has gradually shifted from new construction work to pavement maintenance and management. Since pavement engineers of the Taipei City Government change frequently, objective data is used to make decisions pertaining to road maintenance in Taipei City instead of relying on engineers' experience. In this study, three methods (ID3, C5.0 and SVM) have been chosen to test for use in the decision-making process related to road maintenance of Taipei City. The results show the correct classification rates of the decision trees are 76.67% (C5.0), 64.52% (ID3), and 66.67% (SVM). The decision tree of C5.0 was compared …
Predicting Cross-Gaming Propensity Using E-Chaid Analysis, Eunju Suh, Matt Alhaery
Predicting Cross-Gaming Propensity Using E-Chaid Analysis, Eunju Suh, Matt Alhaery
UNLV Gaming Research & Review Journal
Cross-selling different types of games could provide an opportunity for casino operators to generate additional time and money spent on gaming from existing patrons. One way to identify the patrons who are likely to cross-play is mining individual players’ gaming data using predictive analytics. Hence, this study aims to predict casino patrons’ propensity to play both slots and table games, also known as cross-gaming, by applying a data-mining algorithm to patrons’ gaming data. The Exhaustive Chi-squared Automatic Interaction Detector (E-CHAID) method was employed to predict cross-gaming propensity. The E-CHAID models based on the gaming-related behavioral data produced actionable model accuracy …
Automatic Classification Of Harmonic Data Using $K$-Means And Least Square Support Vector Machine, Hüseyi̇n Eri̇şti̇, Vedat Tümen, Özal Yildirim, Belkis Eri̇şti̇, Yakup Demi̇r
Automatic Classification Of Harmonic Data Using $K$-Means And Least Square Support Vector Machine, Hüseyi̇n Eri̇şti̇, Vedat Tümen, Özal Yildirim, Belkis Eri̇şti̇, Yakup Demi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, an effective classification approach to classify harmonic data has been proposed. In the proposed classifier approach, harmonic data obtained through a 3-phase system have been classified by using $k$-means and least square support vector machine (LS-SVM) models. In order to obtain class details regarding harmonic data, a $k$-means clustering algorithm has been applied to these data first. The training of the LS-SVM model has been realized with the class details obtained through the $k$-means algorithm. To increase the efficiency of the LS-SVM model, the regularization and kernel parameters of this model have been determined with a grid …