A review of the application of data mining techniques for decision making in agriculture
N Gandhi, LJ Armstrong - 2016 2nd International Conference …, 2016 - ieeexplore.ieee.org
This paper provides a review of research on the application of data mining techniques for
decision making in agriculture. The paper reports the application of a number of data mining …
decision making in agriculture. The paper reports the application of a number of data mining …
Rice crop yield prediction in India using support vector machines
N Gandhi, LJ Armstrong, O Petkar… - … 13th International Joint …, 2016 - ieeexplore.ieee.org
Food production in India is largely dependent on cereal crops including rice, wheat and
various pulses. The sustainability and productivity of rice growing areas is dependent on …
various pulses. The sustainability and productivity of rice growing areas is dependent on …
A review on prediction of crop yield using machine learning techniques
Population is increasing day by day in India and demand for food is also increasing, due to
this reason, agriculture is very essential. Advanced technologies like data mining …
this reason, agriculture is very essential. Advanced technologies like data mining …
Big data and machine learning for crop protection
Crop protection is the science and practice of managing plant diseases, weeds and other
pests. Weed management and control are important given that crop yield losses caused by …
pests. Weed management and control are important given that crop yield losses caused by …
Rice crop yield prediction using artificial neural networks
N Gandhi, O Petkar… - 2016 IEEE Technological …, 2016 - ieeexplore.ieee.org
Rice crop production contributes to the food security of India, more than 40% to overall crop
production. Its production is reliant on favorable climatic conditions. Variability from season …
production. Its production is reliant on favorable climatic conditions. Variability from season …
A survey of the applications of Bayesian networks in agriculture
The application of machine learning to agriculture is currently experiencing a “surge of
interest” from the academic community as well as practitioners from industry. This increased …
interest” from the academic community as well as practitioners from industry. This increased …
Prediction of wheat production using machine learning algorithms in northern areas of Pakistan
MU Ahmed, I Hussain - Telecommunications policy, 2022 - Elsevier
New avenues of technological opportunities in agriculture are opening as we are further
delving deeper into the 21st century, but at the same time, new challenges are emerging …
delving deeper into the 21st century, but at the same time, new challenges are emerging …
DeepCropNet: a deep spatial-temporal learning framework for county-level corn yield estimation
Large-scale crop yield estimation is critical for understanding the dynamics of global food
security. Understanding and quantifying the temporal cumulative effect of crop growth and …
security. Understanding and quantifying the temporal cumulative effect of crop growth and …
Machine learning based pedantic analysis of predictive algorithms in crop yield management
M Chandraprabha, RK Dhanaraj - 2020 4th International …, 2020 - ieeexplore.ieee.org
Predictive analytics is a statistical technique used to forecast and investigate the
development from past chronological data or to extract the information from data. With the …
development from past chronological data or to extract the information from data. With the …
A machine learning approach to predict crop yield and success rate
In India agriculture contributes approximately 23% of GDP and employed workforce
percentage is 59%. India is the second-largest producer of agriculture crops. the …
percentage is 59%. India is the second-largest producer of agriculture crops. the …