A Genetic Programming based Algorithm for Predicting Exchanges in Electronic Trade using Social Networks’ Data

Poor, Shokooh Sheikh Abooli; Shiri, Mohammad Ebrahim

doi:10.14569/ijacsa.2017.080524

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…Analysis of users’ behaviour and the herding among them can better predict their future behaviour ( David et al, 2003 ); consumer preferences can be predicted based on the content of keywords and purchase behaviour entered by consumers ( Kim et al, 2001 ; Liu and Toubia, 2018 ); and companies can predict user churn by tracking consumers’ behaviour related to emails ( Ascarza et al, 2018 ). In addition, the prediction of app ad conversions ( Olivier et al, 2014 ) and e-commerce transactions ( Sheikh and Ebrahim, 2017 ) have also received attention from scholars.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on the Evaluation of Cross-Border E-Commerce Overseas Strategic Climate Based on Decision Tree and Adaptive Boosting Classification Models

Lei

Qiu

2021

Front. Psychol.

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At present, China’s cross-border e-commerce has ushered in a golden period of development. When developing cross-border e-commerce, enterprises should first assess the market climate of the target country and reasonably select the target country. Based on the PESTEL theory, an evaluation index system is established for China’s cross-border e-commerce overseas strategic climate. Taking “One Belt, One Road” as the opportunity and background, the overseas strategic climate of cross-border e-commerce in 62 countries along the “One Belt, One Road” is selected as the research object, and the Decision Tree and Adaptive Boosting classification methods in machine learning are applied to train and predict the established index system. Finally an overall picture of the overseas strategic climate of the 62 countries is obtained. The results are compared and analysed in depth to identify the most suitable countries for cross-border e-merchants and to provide reference for cross-border e-merchants investors.

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Section: Literature Reviewmentioning

confidence: 99%

Research on the Evaluation of Cross-Border E-Commerce Overseas Strategic Climate Based on Decision Tree and Adaptive Boosting Classification Models

Lei

Qiu

2021

Front. Psychol.

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The Use of Data Mining Techniques in Predicting the Noise Emitted By the Trailing Edge of Aerodynamic Objects

Shaltooki

Jamshidi

2019

JOIV : Int. J. Inform. Visualization

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Aerodynamic is a branch of fluid dynamics that evaluates the behavior of airflow and its interaction with moving objects. The most important application of aerodynamic is in aerospace engineering, designing and construction of flying objects. Reduction of noise emitted by aerodynamic objects is one of the most important challenges in this area and many efforts have been to reduce its negative effects. The prediction of noise emitted from these aerodynamic objects is a low-cost and fast approach that can partially replace the "fabrication and testing" phase. One of the most common and successful tools in prediction procedures is data mining technology. In this paper, the performance of different data mining algorithms such as Random Forest, J48, RBF Network, SVM, MLP, Logistic, and Bagging is evaluated in predicting the amount of noise emitted from aerodynamic objects. The experiments are conducted on a dataset collected by NASA, which is called "Airfoil Self-Noise". The obtained results illustrate that the proposed hybrid model derived from the combination of Random Forest and Bagging algorithms has better performance compared to other methods with an accuracy of 77.6% and mean absolute error of 0.2279.

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A Genetic Programming based Algorithm for Predicting Exchanges in Electronic Trade using Social Networks’ Data

Cited by 2 publications

References 19 publications

Research on the Evaluation of Cross-Border E-Commerce Overseas Strategic Climate Based on Decision Tree and Adaptive Boosting Classification Models

Research on the Evaluation of Cross-Border E-Commerce Overseas Strategic Climate Based on Decision Tree and Adaptive Boosting Classification Models

The Use of Data Mining Techniques in Predicting the Noise Emitted By the Trailing Edge of Aerodynamic Objects

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