Paper Title
Predicting the Future Impact of Climate Change on the Agriculture Economy

Abstract
The growing Climate Change is not a topic to be assuredly scanned through because it badly impacts the Farmstead, Beasts, Woodland, and Fisheries. According to food services and other Agriculture-related Industries, The Agriculture, and Food Sectors contribute more than $750 billion to GDP(Gross Domestic Product). Climate change leads to decreasing crop production, so now we face trouble feeding our population. Drought and floods are challenges for farmers and threaten food safety due to high temperatures resulting in a decrease in Nutrient level, Soil Moisture, Water Availability, increase in Parasites, and Plant Diseases. According to the United States Environmental Protection Agency from 2010 to 2012 high night-time temperatures affected corn yield in the United States, and Unseasonable Budding due to warm winter caused a $220 million loss of Michigan cherries in 2012. It also badly impacts Fisheries Culture, and U.S. fisheries chip in more than $1.55 billion to the United States Economy. Hence, there is a need for action. The concern is that we do not have a specific model to predict our future Agriculture conditions influenced by climate change with a good accuracy percentage. So, taking the lead data from contemporary scientific and conceptual work on climate change from various journals. Focusing on the factors and parameters which impact Agricultural Activities we take multitudinous parameters for this research like temperature, Rainfall, Increase in Atmospheric CO2, Fluctuations in Sea Levels, Drought, Heat Stress, Soil Properties, Soil Salinity, Flood, Diseases, Pests, and Acidity Stress. The paper illustrates this approach about the future Agriculture Economy of the Agriculture field due to climate change using Machine Learning Algorithms. Keywords - Machine Learning, Agriculture, Economy, Climate Change, Rainfall.