HOW CLIMATE OF WORLD IS CHANGINGWHY DO WE NEED AGRICULTURE?AGRICULTURE AND CLIMATESince the Industrial Revolution, Earth’s climate has been changing fast. Human actions are the major factor promoting this intense pace. In particular, the massive use of fossil fuel (oil, charcoal, gas) releases a large amount of carbon dioxide (CO2), nitrogen dioxide (N2O), methane (CH4), Chlorofluorocarbon(CFC-11) and Chlorofluorocarbon(CFC-12) into the atmosphere, which concentrates, and warms the planet. So far, this climate change has not affected life on Earth too much. However, it is threatening the existence of several life forms that have to endure this climate change coupled with other human-induced changes (for example, deforestation). All these factors combined may soon affect us, too. For instance, the availability of food may be drastically reduced.Agriculture plays a critical role in the entire life of a given economy. Agriculture is the backbone of the economic system of a given country. In addition to providing food and raw material, agriculture also provides employment opportunities to a very large percentage of the population.Changes in ozone, greenhouse gases and climate change affect agricultural producers greatly because agriculture and fisheries depend on specific climate conditions. Temperature changes can cause habitat ranges and crop planting dates to shift and droughts and floods due to climate change may hinder farming practices.
OUR PROJECT
DATA ANALYSISPrediction
MACHINE LEARNING
There were two different analysis based on the requirements: “Greenhouse gases – Climate”, “Climate – Crops”. The analysis of Greenhouse gases – Climate tells us how greenhouse gases effect Climate. The analysis of Climate – Crops tells us how climate conditions (Annual Precipitation, Average Temperature per year) and some other conditions such as Soil Type, Irrigation Area effect the production of crops.In the project we have used Random Forest Model for the Prediction of crops on the basis of climate conditions and used Decision Tree, Naïve Byes, Random Forest, Support Vector Machine (SVM) model and Logistic Regression to predict climate condition on the basis of scoring technique.Given the machine learning models we run the dataset on each model and used a scoring technique i.e. the answer with the most votes from each model will be the final prediction. If there is a tie between the answer than the answer given by the model whose accuracy is the most will be the final prediction.