Impact Factor:6.549
 Scopus Suggested Journal: Tracking ID for this title suggestion is: 55EC484EE39417F0

International Journal
of Computer Engineering in Research Trends (IJCERT)

Scholarly, Peer-Reviewed, Platinum Open Access and Multidisciplinary




Welcome to IJCERT

International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed, Platinum Open Access and Multidisciplinary

ISSN(Online):2349-7084                 Submit Paper    Check Paper Status    Conference Proposal

Back to Current Issues

Dynamic Crop-yield and Price Forecasting using Machine Learning

Chaitra Kotnikall, Jayateerth Vadavi, , ,
Affiliations
1*Student, Dept. Of CSE, Shri Dharmasthala Manjunatheshwara College of Engineering, Dharwad, India. 2: Associate Professor, Dept. Of CSE, Shri Dharmasthala Manjunatheshwara College of Engineering, Dharwad, India.
:10.22362/ijcert/2020/v7/i06/v7i0607


Abstract
Background: Guaranteeing food profitability is a significant issue for creating nations like India, where more than 33% of the individuals is live in neediness. To estimate cost, there is no system in place to advise farmers what crops to grow. Hence, this paper explains the attempt to predict crop price that a farmer can obtain from his land by analyzing patterns in past data. Methods/Statistical analysis: This method makes use of several data such as rainfall, temperature, market prices, and past yield of a crop. The supervised machine learning algorithm, namely, the Decision tree algorithm and analyse the data and predict for the new set of data, is implemented. It also predicts the price and the gain for the next twelve months over the past twelve months and gives the time series analysis of the same. Findings: The proposed model is developed to help farmers make better decisions concerning which crop is most suitable during his desired time of sowing and the location. This System predicts the yield and price of the crop of choice, giving the farmer useful information well before starting the process of cultivation. Improvements: The System can introduce and make available climate-aware cognitive farming techniques and identifying systems of crop monitoring, early warning on pest/disease outbreak based on advanced AI innovation.


Citation
Chaitra Kotnikall, Jayateerth Vadavi."Dynamic Crop-yield and Price Forecasting using Machine Learning ". International Journal of Computer Engineering In Research Trends (IJCERT) , ISSN:2349-7084, Vol.7, Issue 06,pp.46-51, June - 2020, URL:http://ijcert.org/ems/ijcert_papers/V7I607.pdf,


Keywords : Crop-yield, Supervised Machine learning in Agriculture, Decision tree, Forecasting, Analysis.

References
[1] S. Kulkarni, S. N. Mandal, G. S. Sharma, M. R. Mundada and Meeradevi, "Predictive Analysis to Improve Crop Yield Using a Neural Network Model," 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Bangalore, 2018, pp. 74-79.
[2] S. V. Bhosale, R. A. Thombare, P. G. Dhemey and A. N. Chaudhari, "Crop Yield Prediction Using Data Analytics and Hybrid Approach," 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), Pune, India, 2018, pp. 1-5.
[3] T. Siddique, D. Barua, Z. Ferdous and A. Chakrabarty, "Automated farming prediction," 2017 Intelligent Systems Conference (IntelliSys), London, 2017, pp. 757-763.
[4] S. Bhanumathi, M. Vineeth and N. Rohit, "Crop Yield Prediction and Efficient use of Fertilizers," 2019 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2019, pp. 0769-0773.
[5] P. Bose, N. K. Kasabov, L. Bruzzone and R. N. Hartono, "Spiking Neural Networks for Crop Yield Estimation Based on Spatiotemporal Analysis of Image Time Series," in IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 11, pp. 6563-6573, Nov. 2016.
[6] N. Hemageetha and G. M. Nasira, "Radial Basis Function Model for Vegetable Price Prediction", International Conference on Pattern Recognition, Informatics and Mobile Engineering, pp. 424-428, 2013
[7] Yung-Hsing Peng, Chin-shun Hsu, and Po-Chuang Huang, "An investigation of Spatial approaches for crop price forecasting in different Taiwan markets",2015.
[8] Prof A K Mariappah and J Austin Ben Das, "A Paradigm for rice yield prediction in Tamil Nadu", IEEE International Conference on Technological Innovations in ICT For Agriculture and Rural Development (TIAR), pp. 18-21, 2017.
[9] J. Hartigan, Clustering Algorithms, John Wiles & Sons, New York, 1975. 
[10] Fagerlund S Bird species recognition using Support Vector Machines. EURASIP J Adv Signal Processing, Article ID 38637, p 8, 2007. 
[11] Holmgren P, Thuresson T Satellite remote sensing for forestry planning: a review. Scand J for Res 13(1):90 110, 1998. 
[12] Das KC, Evans MD Detecting fertility of hatching eggs using machine vision II: Neural Network classifiers. Trans ASAE 35(6):20352041, 1992.


DOI Link : https://doi.org/10.22362/ijcert/2020/v7/i06/v7i0607

Download :
  V7I607.pdf


Refbacks : Currently there are no Refbacks

Support Us


We have kept IJCERT is a free peer-reviewed scientific journal to endorse conservation. We have not put up a paywall to readers, and we do not charge for publishing. But running a monthly journal costs is a lot. While we do have some associates, we still need support to keep the journal flourishing. If our readers help fund it, our future will be more secure.

Quick Links



DOI:10.22362/ijcert


Science Central

Score: 13.30





Submit your paper to editorijcert@gmail.com