An LSTM-Driven Model for Accurate Agricultural Pest Risk Prediction
This research aims to build an effective predictive modeling system for agricultural pest risk using machine learning techniques and weather conditions. The study focuses on increasing prediction accuracy by checking deep learning models to help with timely and correct pest management decisions. In this research, we sa...