Training Students with Data Mining and GIS
Keywords:Data Mining, GIS, SOM, Classificaion
Present in colleges to day the students have course of the data mining which is the procedure of mining knowledge from data to solve problems, gain knowledge and set expectations. Students in the course have acquired a great knowledge and understanding of the processes involved in extracting data through the experience gained in data extraction applications. The course has shown that students' education is appropriate and can be successful. In this research students apply their expertise on data taken from the Iraqi Health Ministry to persons infected with hepatitis in Iraq's cities to discover knowledge about the virus, and that the use of geographic information system (GIS) to display the result to extract the data in the map of Iraq, which give force for them work and that new way to combine data mining with GIS.
 Witten, I., Frank E. (2000). Data Mining. Academic Press.
 Sullivan, T. (2000) â€œEMC's Ruettgers warns of data explosion.â€ InfoWorld.comhttp://www.infoworld.com/articles/hn/xml/00/10/04/001004hnruettgers.xml?spon sor=STORAGE
 Shakeel, P.M., Tolba, A., Al-Makhadmeh, Zafer Al-Makhadmeh, Mustafa Musa Jaber, â€œAutomatic detection of lung cancer from biomedical data set using discrete AdaBoost optimized ensemble learning generalized neural networksâ€, Neural Computing and Applications,2019,pp1-14.https://doi.org/10.1007/s00521-018-03972-2
 University of Waikato. â€œWeka 3 â€“ Machine Learning Software in c++.â€ http://www.cs.waikato.ac.nz/ml/weka/
 Knowledge Seeker Data Mining Tool. â€œAngoss Home Page.â€ http://www.angoss.com/
 U. S. Forest Service. (1992). â€œThe Eastwide Forest Inventory Database Userâ€™s Manual.â€ http://srsfia.usfs.msstate.edu/ewman.htm
 Whalin, P. (2000) â€œData Mining Research.â€
 Ludwig, L., Flies, D., Wilson, A. (2000) â€œData Mining Techniques Applied to the Relationship of Latitude and the Lifespan of Aspen Treesâ€ http://epoxy.mrs.umn. edu ~ludwigl/datamining/research.pdf
 JOHN PICKLES (2003)"GIS for the urban environment" PRINTED IN USA CROWN5M 7/06DH PRODECT BY ESRI Ministry of health.
 Preeth, S.K.S.L., Dhanalakshmi, R., Kumar, R.,Shakeel PM.An adaptive fuzzy rule based energy efficient clustering and immune-inspired routing protocol for WSN-assisted IoT system.Journal of Ambient Intelligence and Humanized Computing.2018:1â€“13. https://doi.org/10.1007/s12652-018-1154-z
 A. Meri et al., â€œModelling the Utilization of Cloud Health Information Systems in the Iraqi Public Healthcare Sector,â€ Telemat. Informatics, 2018.
 P. M. Shakeel, S. Baskar, V. R. S. Dhulipala, and M. M. Jaber, â€œCloud based framework for diagnosis of diabetes mellitus using K-means clustering,â€ Heal. Inf. Sci. Syst., vol. 6, no. 1, p. 16, 2018.
 P. M. Shakeel, S. Baskar, V. R. S. Dhulipala, S. Mishra, and M. M. Jaber, â€œMaintaining security and privacy in health care system using learning based Deep-Q-Networks,â€ J. Med. Syst., vol. 42, no. 10, p. 186, 2018.
 M. A. Mohammed et al., â€œGenetic case-based reasoning for improved mobile phone faults diagnosis,â€ Comput. Electr. Eng., 2018.
 M. Jarrar, M. S. Minai, M. Al-Bsheish, A. Meri, and M. Jaber, â€œHospital nurse shift length, patient-centered care, and the perceived quality and patient safety,â€ International Journal of Health Planning and Management, 2018.
 Shakeel PM. Neural Networks Based Prediction Of Wind Energy Using Pitch Angle Control. International Journal of Innovations in Scientific and Engineering Research (IJISER). 2014;1(1):33-7.
 M. T. Naseem et al., â€œPreprocessing and signal processing techniques on genomic data sequences,â€ Biomed. Res., vol. 28, no. 22, 2017.
 M. H. Ali, M. F. Zolkipli, M. A. Mohammed, and M. M. Jaber, â€œEnhance of extreme learning machine-genetic algorithm hybrid based on intrusion detection system,â€ J. Eng. Appl. Sci., vol. 12, no. 16, 2017.
 M. H. Ali, M. F. Zolkipli, M. M. Jaber, and M. A. Mohammed, â€œIntrusion detection system based on machine learning in cloud computing,â€ J. Eng. Appl. Sci., vol. 12, no. 16, 2017.
 Integrating GIS and Spatial Data Mining Techniques for Target marketing of University Courses | Request PDF. Available from: https://www.researchgate.net/publication/228529975_Integrating_GIS_and_Spatial_Data_Mining_Techniques_for_Target_marketing_of_University_Courses [accessed Nov 05 2018].
 El-Halees, A. (2008), Mining students data to analyze learning behavior: a case study,
 Flies, D. (2001) â€œDesigning & Implementing a Classroom Data Warehouse.â€MICS.
 P. Mohamed Shakeel; Tarek E. El. Tobely; Haytham Al-Feel; Gunasekaran Manogaran; S. Baskar., â€œNeural Network Based Brain Tumor Detection Using Wireless Infrared Imaging Sensorâ€, IEEE Access, 2019, Page(s): 1
 L. Haoyu, L. Jianxing, N. Arunkumar, A. F. Hussein, and M. M. Jaber, â€œAn IoMT cloud-based real time sleep apnea detection scheme by using the SpO2 estimation supported by heart rate variability,â€ Futur. Gener. Comput. Syst., 2018.
 S. K. Abd, S. A. R. Al-Haddad, F. Hashim, A. B. H. J. Abdullah, and S. Yussof, â€œEnergy-Aware Fault Tolerant Task offloading of Mobile Cloud Computing,â€ in Proceedings - 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2017, 2017.