Family farms play a role in economic development. Limited terms of land, water and capital resources, family farming is essentially characterized by its use labour. must choose which agricultural products to produce; however, they do not have the necessary tools for optimizing their decisions. Knowing will best prices at harvest important farmers. At this point, machine learning technology has ...

Accurate stock price prediction has an important role in investment. Because data are characterized by high frequency, nonlinearity, and long memory, predicting prices precisely is challenging. Various forecasting methods have been proposed, from classical time series to machine-learning-based methods, such as random forest (RF), recurrent neural network (RNN), convolutional (CNN), Long Short-T...

Abstract The Turkish Housing Market has experienced a steep increase in prices. Individual and corporate investors now possess tools to estimate the real estate evaluation while using smaller amounts of data with traditional techniques. Not having an analytical approach evaluate price could cause investor lose considerable money, especially case individual investors. This study aims determine h...

In recent years, many investors have used cryptocurrencies, prompting specialists to find out the factors that affect cryptocurrencies’ prices. Therefore, one of most popular methods been predict cryptocurrency prices is sentiment analysis. It a widespread technique utilized by researchers on social media platforms, particularly Twitter. Thus, determine relationship between investors’ and volat...

The research purpose of this paper is to obtain an algorithm model with high prediction accuracy for the price Bitcoin on next day through random forest regression and LSTM, explain which variables have influence Bitcoin. There much prior literature research, methods mainly revolve around ARMA time series LSTM deep learning. Although it cannot be proved by Diebold–Mariano test that significantl...

House price fluctuates each and every year due to changes in land value change infrastructure around the area. Centralised system should be available for prediction of house correlation with neighbourhood infrastructure, will help customer estimate house. Also, it assists come a conclusion where buy when purchase Different factors are taken into consideration while predicting worth like locatio...