Avocado Price Prediction Using a Hybrid Deep Learning Model: TCN-MLP-Attention Architecture

Understand

With the growing demand for healthy foods, agricultural product price forecasting has become increasingly important.

• Hass avocados, as a high-value crop, exhibit complex price fluctuations influenced by factors such as seasonality, region, and weather.
• Traditional prediction models often struggle with highly nonlinear and dynamic data.
• To address this, we propose a hybrid deep learning model, TCN-MLP-Attention Architecture, combining Temporal Convolutional Networks (TCN) for sequential feature extraction, Multi-Layer Perceptrons (MLP) for nonlinear interactions, and an Attention mechanism for dynamic feature weighting.