A Survey on Crop Yield Prediction using Data Mining
MLA Style: Mythra.N, Dr.Velayudham.A, Dr.Shamila.E.S, Pavithra.M "A Survey on Crop Yield Prediction using Data Mining" International Journal of Computer Trends and Technology 65.1 (2018): 1-7.
APA Style:Mythra.N, Dr.Velayudham.A, Dr.Shamila.E.S, Pavithra.M (2018). A Survey on Crop Yield Prediction using Data Mining. International Journal of Computer Trends and Technology, 65(1), 1-7.
Abstract
Now-a –days the most important emerging field in the real world is agriculture and it is the main occupation and backbone of our country. The most of the primary and secondary business is based on farming and it plays the main role in our Indian economy. In farming, season cultivation of the crop is based on the soil. Another important work in agriculture is selecting soil is based on the weather condition and also when to harvest the crop for the best cultivation. Data mining techniques is very popular in the Area of agriculture. Data mining is the process of finding the new templates from the large data sets there are various data mining techniques are used and evaluated in agriculture for estimating the future year’s crop production. Utilization of information and communications technology enables automation of extracting significant data in an effort to obtain knowledge and trends crop is an essential key factor of agriculture. So data mining techniques are useful for new framers. This paper presents a brief comparative study of various papers that deals with various techniques used to figure out the crop yield different data mining techniques that are in the use for crop yield estimation in agriculture. Recently data processing techniques in agriculture required decide, storage, monitored and retrieval the resource used this survey aims to search out appropriate data processing models to realize high accuracy and prediction capabilities.
Reference
[1] Rajeswari and k.arunesh, “Analysing Soil Data using Data Mining classification techniques”, Indian Journal of science and Technology,Volume 9(19), DOI: 10.17485/ijst/2016/v9i19/93873, May 2016.
[2] K. L. Ponce-Guevara1, J. A. Palacios-Echeverr´?a1, E. Maya-Olalla1, H. M. Dom´?nguez-Limaico1,L. E. Su´arez-Zambrano1, P. D. Rosero-Montalvo1,4, D. H. Peluffo-Ord´o˜nez1,2, and J. C. Alvarado-P´erez2, “Green Farm-DM: A tool for analysing vegetable crops data from a greenhouse using data mining techniques(First trial)”, 978-1-5386-3894-1/17/$31.00 ©2017IEE.
[3] D Ramesh, B Vishnu vardhan, “ANALYSIS OF CROP YEILD PREDICTION USING DATA MINING TECHNIQUES”, IJRET: International Journal of Research in engineering and Technology, volume: 04, Issue: 01, jan-2015.
[4] Available @ http://www.ijret.org
[5] Aakunuri Manjula and Dr.G.Narsimha, “Crop Yield Predictionwith Aid of Optimal Neural Network in Spatial Data Mining: NewApproaches”, InternationalJournal of Information & Computation Technology, ISSN 0974-2239 volume 6, Number1, pp. 25-33, 2016.
[6] © International Research Publications House http://www. irphouse.com.
[7] A. K. Tripathy, J. Adinarayana, D. Sudharsan, K. Vijayalakshmi , S. N. Merchant, U. B.Desai, “Data Mining and Wireless Sensor Network for Groundnut Pest/Disease Interaction and predictions –A Preliminary Study”, International Journal of Computer Information Systems and Industrial Management Applications, ISSN 2150-7988 Volume 5,pp. 427-436,©2013.
[8] www.mirlabs.net/ijcisim/index.html.
[9] S. Hari Ganesh, Mrs. Jayasudha, “Data Mining Technique to Predict the Accuracy of the soil Fertility ”,International Journal of Computer Science and Mobile Computing (IJCSMC),volume 4,Issue 7 ,pg.330-333,july 2015.
[10] B. Milovi and V. Radojevi, “APPLICATION OF DATA MINING IN AGRICULTURE”, Bulgarian journal of agricultural science, 21(No 1) 26-34agricultural academy, 2015.
[11] R S. Kodeeshwari, K. Tamil, “Different Types of Data Mining Techniques Used in Agriculture –A Survey “International Journal of Advanced Engineering Research and Science (IJAERS), vol-4, Issue-6s, Jun-2017.
[12] https://dx.doi.org/10.22161/ijaers.4.6.3.
[13] Huma Khan, Shahista Navaz, Dr. S. M. Ghosh, “A Survey on Various Data Mining Techniques in Field of Agriculture for Prediction of Crop Yields”, International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2015): 78.96 | Impact Factor, 2015.
[14] Suvidha Jambekar, Shikha Nema ,Zia Saquib, “Data Mining Techniques for Prediction of Crop Production in India”, International Journal of Innovations &Advancement in Computer Science(IJIACS),ISSN 2347 – 8616,Volume 7, Issue 4,April 2018.
[15] Ramesh A, Vijay. S. Rajpurohit, “A survey on Data Mining Techniques for Crop Yield Prediction”, “International Journal of Advance Research in Volume 2, Issue 9, September 2014”.
[16] Zekarais Dirida,Berhanu borena, “application of data mining techniques for crop productivity prediction”, “HiLcoE journal of computer science and technology ’’vol.1novmeber.2015
[17] Dakshayini Patil,Dr.M.S.shirdhonkar, “rice crop yield prediction using data mining techniques”, “International journal of advanced research in computer science and software engineering ”volume7,issue 5,may2017
[18] DR.A.Senthil Kumar,P.Arun, “A survey on agriculture for crop yield prediction using data mining techniques”, “IOSR journal of computer engineering (ISOR-JCE)p.no23-25,vol 6,issue 3,March 2017
[19] Yogesh gandge,sandhya, “A study on various data mining techniques for crop yield prediction, , “ international conference on computer and optimization techniques (ICEECCOT), 978-1-5386-2361-9/17/$31.00 ©2017 IEEE
Keywords
Data Mining, Agriculture, framer, Crop Selection, soil selection, methodology, high accuracy, prediction capabilities.