| References: [1] Mohanty, A. K. Senapati, M. R., Lenka, S. K. (2016). Retraction Note to: An improved data mining technique for classification and detection of breast cancer from mammograms. Neural Computing and Applications, 27(1), 249-249.
[2] Robson, B., Boray, S. (2016). Data-mining to build a knowledge representation store for clinical decision support. Studies on curation and validation based on machine performance in multiple choice medical licensing examinations. Computers in Biology & Medicine, 73, 71.
[3] Hong, H., Pourghasemi, H. R., and Pourtaghi, Z. S. (2016). Landslide susceptibility assessment in Lianhua County (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models. Geomorphology, 259, 105-118.
[4] Rathod, R. R., Garg, R. D. (2016). Regional electricity consumption analysis for consumers using data mining techniques and consumer meter reading data. International Journal of Electrical Power and Energy Systems, 78, 368-374.
[5] Bandaru, S., Ng, A. H. C., Deb, K. (2017). Data mining methods for knowledge discovery in multi-objective optimization: Part B - New developments and applications. Expert Systems with Applications, 70, 119-138.
[6] Giabbanelli, P. J., Jean, A. (2016). Identifying small groups of foods that can predict achievement of key dietary recommendations: data mining of the UK National Diet and Nutrition Survey, 2008–12. Public Health Nutrition, 19(9), 1.
[7] Wu, W., Peng, M. (2017). A Data Mining Approach Combining K-Means Clustering With Bagging Neural Network for Short- Term Wind Power Forecasting. IEEE Internet of Things Journal, 4(4), 979-986.
[8] Tayefi, M., Tajfard, M., Saffar, S., et al. (2017). hs-CRP is strongly associated with coronary heart disease (CHD): A data mining approach using decision tree algorithm. Computer Methods and Programs in Biomedicine, 141, 105-109.
[9] Chen, W., Pourghasemi, H. R., Naghibi, S. A. (2017). Prioritization of landslide conditioning factors and its spatial modeling in Shangnan County, China using GIS-based data mining algorithms. *Bulletin of Engineering Geology and the Environment, 1- 19.
[10] Alborzi, M., Khanbabaei, M. (2016). Using data mining and neural networks techniques to propose a new hybrid customer behavior analysis and credit scoring model in banking services based on a developed RFM analysis method. International Journal of Business Information Systems, 23(1), 1. |
