International Journal of Knowledge Engineering and Data Mining
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International Journal of Knowledge Engineering and Data Mining (3 papers in press)
Study on the Electric Vehicle Sales Forecast with TEI@I Methodology by Jiang Ping Wan, Le Qi Xie, Xue Fang Hu Abstract: The research was decomposition and integration based on TEI@I methodology: the prediction model applied principal component regression analysis (PCR) to deal the linear relationship, and then applied BP neural network and support vector machine (SVM) to deal the nonlinear relationship, and finally, they are all integrated together. Granger causality test and grey correlation degree are used to quantitatively analyze the factors affecting the sales of electric vehicles through mining consumer network data, The research results of electric vehicle models show that the Baidu search index lags behind for three months is time-sensitive to the sales of electric vehicles. Finally, taking the data of two car models as examples, it is found that the PCR-BP model and the PCR-SVM model have better prediction performance than the single model. Keywords: electric vehicle sales forecast; CiteSpace; TEI@I methodology; principal component regression analysis; BP neural network; support vector machine; Baidu search index. DOI: 10.1504/IJKEDM.2020.10030715
Improving E-Health Governance through Syndromic Surveillance Systems and Data Mining in KSA by Ghada Al Omran Abstract: Recently, the KSA has witnessed significant technical advances in health sector, where local hospitals are using high-quality systems and technologies to serve patients. However, even with this high progress in healthcare systems, the communication is still limited with other decision makers in different sectors whose need to access some health-related information to take the best decisions for serving patients. Therefore, this project aims to utilise from the concept of electronic health governance (e-health governance) to build an automated system, which will help the health sector to know common coming diseases and facilitate the decision-making process through providing them with the necessary health information to help them provide the best service for patients in various fields. To do that this research will apply classification data mining techniques through using naive Bayes classification algorithm; where this project aims to build a common diseases prediction system (CDPS) to working as syndromic surveillance system. Keywords: data mining; electronic governance; syndromic surveillance system; SSS; naive Bayesian; common disease prediction system. DOI: 10.1504/IJKEDM.2020.10035583
The impacts of Knowledge Management on Organizational Entrepreneurship with the Moderating Role of Social Capital in the Melli Bank (Mashhad Branches) by Bahare Khayyami, Amirali Motamedi, Elham Shadkam Abstract: The main goal of this research is the relationship between knowledge management and entrepreneurship with the role of social capital adjustment in Melli banks employees. The sample was analysed using Cochran table and two-stage cluster sampling that 117 employees of the Mashhads Mellis bank. In this research, four standard questionnaires are used to measure the variables under study. The results of this study showed: there is a relationship between knowledge management and organisational entrepreneurship and the social capital has a moderating effect on knowledge management and entrepreneurship. Keywords: knowledge management; social capital; enterprise entrepreneurship; Melli Bank; laser. DOI: 10.1504/IJKEDM.2020.10037411