Premasundari M Shivakumar, Dr. C. Yamini


Agriculture is the backbone of India. The ultimate goal of farming is the cultivation and perfection of human beings. Agriculture acts as a mediator between nature and the human community. Soil is the boon for agriculture and chemical fertilizer is the curse for soil. Food produced by these artificial fertilizers causes many challenges to human lives. Autism Spectrum Disorder is the third most common developmental disorder. The first ever survey shows that more than 10 million children in India suffer from autism. Data Mining is one of the phases involved in Knowledge Discovery in Databases. The goal of Data mining is the discovery of patterns and knowledge from large datasets. There are a number of machine learning techniques such as classification, clustering, association rule etc. involved in data mining. Classification belongs to supervised learning technique of data mining. This research work focuses on finding whether agriculture has any impact on autism. This paper shows the literature review based on the significance of prediction and classification based data mining algorithms in the field of agriculture and autism spectrum disorder.


Classification; Autism; Crop yield; Rainfall Prediction; Support Vector Machine; J48; REPTree; Neural Network; Fuzzy Logic

Full Text:




Arun K Pujari, “Data Mining Techniques”, University Press 2001.


M.S.Mythili, A.R.Mohamed Shanavas, “A Study on Autism Spectrum Disorders using Classification Techniques”, International Journal of Soft Computing and Engineering (IJSCE), Vol.4 Issue-5, Pp.88-91, November 2014.

Mohana E, Poonkuzhali.S, “Categorizing The Risk Level Of Autistic Children Using Data Mining Techniques”, International Journal of Advance Research In Science And Engineering IJARSE, Vol. No.4, Special Issue (01), Pp.223-230, April 2015.

Sumi Simon, Chandra J and Saravanan N, “Empirical Evaluation of Data Mining Classification Methods for Autistic Children”, Special Issue Published in International Journal of Trend in Research and Development (IJTRD), Pp.7-10, February 2016.

M.S.Mythili, A.R.Mohamed Shanavas, “A Novel Approach to Predict the Learning Skills of Autistic Children using SVM and Decision Tree”, International Journal of Computer Science and Information Technologies, Vol. 5 (6), Pp.7288-7291, 2014.

G. Leroy, A. Irmscher, and M.H. Charlop-Christy, "Data Mining Techniques to Study Therapy Success with Autistic Children", 2006 International Conference on Data Mining, 26 - 29 June 2006, Monte Carlo Resort, Las Vegas, USA.

Rajshekhar Borate, Rahul Ombale, Sagar Ahire, Manoj Dhawade, and Mrs. Prof. R. P. Karande, “Applying Data Mining Techniques to Predict Annual Yield of Major Crops and Recommend Planting Different Crops in Different Districts in India”, International Journal of Novel Research in Computer Science and Software Engineering Vol. 3, Issue 1, Pp.34-37, January-April 2016.

D Ramesh , B Vishnu Vardhan, “ Analysis of Crop Yield Prediction using Data Mining Techniques”, International Journal of Research in Engineering and Technology, Vol. 04 Issue 01, Pp.470-473, Jan-2015.

Zekarias Diriba, Berhanu Borena, “Application of Data Mining Techniques for Crop Productivity Prediction”, HiLCoE Journal of Computer Science and Technology, Vol. 1, No. 2, Pp.152-155.

M.Kannan, S.Prabhakaran, P.Ramachandran, “Rainfall Forecasting Using Data Mining Technique”, International Journal of Engineering and Technology, Vol.2 (6), Pp.397-401, 2010.

Dr. S.Hari Ganesh, Mrs. Jayasudha, “Data Mining Technique to Predict the Accuracy of the Soil Fertility”, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.7, Pp. 330-333, July- 2015.

DOI: https://doi.org/10.26483/ijarcs.v8i7.4382


  • There are currently no refbacks.

Copyright (c) 2017 International Journal of Advanced Research in Computer Science