1. Baisen, Z., and R. Tillman. 2007. A decision tree approach to modeling nitrogen fertilizer use efficiency in New Zealand pasture. Plant and Soil 301 (1): 267-278.
2. Breman, L., Friedman, J., Olshen, R., and Ch. Stone. 1984. Classification and regression trees. Boca Raton: Chapman & Hall/CRC.
3. Choi, J., K. H. Jeon, Y. Won, and J. J. Kim. 2014. Pattern classification of foot diseases using decision tree. Wseas Transactions on Biology and Biomedicine 11: 157-164.
4. Ekasingh, B., and K. Ngamsomsuke. 2009. Searching for simplified farmers’ crop choice models for integrated watershed management in Thailand: A data mining approach. Environmental Modeling and Software 24: 1373-1380.
5. Geetha, M. C. S. 2015. A survey on data mining techniques in agriculture. International Journal of Innovative Research in Computer and Communication Engineering 3 (2): 887-892.
6. Goktepe, A. B., S. Altun, and A. Sezar. 2005. Soil clustering by fuzzy C-Means algorithm. Advances in Engineering Software 36: 691-698.
7. Jeysenthil, K. M. S., T. Manikandan, and V. Murali. 2014. Third generation agricultural support system development using data mining. International Journal of Innovative Research in Science, Engineering and Technology 3 (3): 9923- 9930.
8. Kalpana, R., N. Shanthi, and S. Arumugam. 2014a. Data mining– An evolutionary view of agriculture. International Journal of Application or Innovation in Engineering and Management 3 (3): 102- 105.
9. Kalpana, R., N. Shanthi, and S. Arumugam. 2014b. a survey on data mining techniques in agriculture. International Journal of Advances in Computer Science and Technology 3 (8): 426-431.
10. Kotsiantis, S. B. 2007. Supervised machine learning: A review of classification techniques. International Journal of Computing and Informatics 31 (3): 249- 268.
11. Monjezi, N., and H. Zakidizaji. 2017. Fuzzy approach to optimize overhaul time of sugarcane harvester using GERT network method. Iranian Journal of Biosystem Engineering 48 (1): 83-91. (In Farsi).
12. Monjezi, N., H. Zakidizaji, M. J. Sheikhdavoodi, A. Marzban, and M. Shomeili. 2017. Finding and prioritizing of effective parameters on lack of timeliness operations of sugarcane production using Analytical Hierarchy Process (AHP). Journal of Agricultural Machinery 7 (2): 514-526. (In Farsi).
13. Noorzadeh, M., K. Khavazi, M. Malakooti, and S. Hashemi. 2011. Evaluation of the effectiveness of C-means and GK methods for fuzzy clustering of copper concentration in agricultural lands (Case study: Hamedan Province). Journal of Agricultural Engineering 33 (1): 61-70. (In Farsi).
14. Quinlan, J. 1993. Programs for machine learning. Morgan Kaufmann, San Francisco, CA, pp.
15. Rajesh, D. 2011. Application of Spatial Data Mining for Agriculture. International Journal of Computer Applications 15 (2): 7-9.
16. Ramesh, D., and B. Vishnu Vardhan. 2013. Data mining techniques and applications to agricultural yield data. International Journal of Advanced Research in Computer and Communication Engineering 2 (9): 3477-3480.
17. Raorane, A. A., and R. V. Kulkarni. 2013. Review- Role of data mining in agriculture. International Journal of Computer Science and Information Technologies 4 (2): 270-272.
18. Razi Ardakani, H., and A. Samimi. 2011. Comparison of decision tree in modeling choosing a type of means of carriage of goods. 11th Transportation and Traffic Engineering. 2-3 February, Tehran. (In Farsi).
19. Sharma, L., and N. Mehta. 2012. Data mining techniques: A tool for knowledge management system in agriculture. International Journal of Scientific and Technology Research 1 (5): 67-73.
20. Umesh, D. R., and C. R. Thilak. 2015. Predicting breast cancer survivability using Naïve Baysien and C5.0 algorithm. International Journal of Computer Science and Information Technology Research 3 (2): 802-807.
21. Yethiraj, N. G. 2012. Applying data mining techniques in the field of agriculture and allied sciences. International Journal of Business Intelligents 1 (2): 72-76.
22. Yoneyama, Y., S. Suzuki, R. Sawa, K. Yoneyama, G. G. Power, and T. Araki. 2002. Increased plasma adenosine concentrations and the severity of preeclampsia. Obstet Gynecol 100 (6):1266-1270.
)
ارسال نظر در مورد این مقاله