Agriculture Crop Yield Forecasting using Deep Learning Techniques

Crop yield predictions offer valuable insights for various peoples such as farmers, policymakers, and commodity traders, guiding them in making strategic decisions concerning food security and market entry. The complex dynamics between crop-specific attributes, environmental conditions, and management practices significantly impact crop yields. This complexity not only poses a challenge in understanding crop yields. Hence, this work proposes a crop yield prophecy model by comparing the deep learning algorithms such as Long ShortTerm Memory (LSTM) and 1-Dimensional Convolutional Neural Network (1DCNN) to find the optimal model for overcoming such difficulties.