@conference {840,
	title = {Predicting Agricultural Product and Supplies Prices using Artificial Intelligence},
	booktitle = {Proceedings of the 16th International Conference on Knowledge Management and Information Systems},
	year = {2024},
	publisher = {SCITEPRESS Digital Library},
	organization = {SCITEPRESS Digital Library},
	abstract = {<p>This work focuses on the prediction of agricultural product and supply prices using historical data and artificial intelligence methods. Agricultural product and supply prices are important for the economy and growth of agriculture. Using modern data analysis and deep learning methods, a forecasting model was developed to help us predict future price trends. The data used include the sales prices of crop products and the purchase prices of agricultural inputs. The developed forecasting methods exhibit high accuracy for predicting the actual prices of products and supplies, with error margins ranging from 0.29\% to 9.8\%, while they can also predict price rises and falls, with respective success rates ranging from 73.29\% to 84.96\%.</p>
},
	keywords = {Agricultural Products, Data Integration, deep learning, Forecasting Models, Machine Learning, Price Forecasting},
	author = {Ioannis Dionissopoulos and Fotis Assimakopoulos and Dimitris Spiliotopoulos and Dionisis Margaris and Costas Vassilakis}
}
