Farmers sometimes grow crops with low yields, wasting land, labor, and time—especially in developing countries where demand for food is increasing. A Crop Recommendation System (CRS) can help by using precision farming techniques that analyze soil and environmental data to suggest the most suitable crops. This study proposes a CRS using a Modified Salp Swarm Algorithm (MSSA) for feature selection and an Adaptive Weighted Bi-directional Long Short-Term Memory (AWBiLSTM) ensemble for prediction. MSSA enhances the original algorithm by improving local search and convergence speed, addressing SSA’s limitations. Climate data is pre-processed and relevant features are selected using MSSA. AWBi... More >