Summary of Agricultural Recommendation System Based on Deep Learning: a Multivariate Weather Forecasting Approach, by Md Zubair (1) et al.
Agricultural Recommendation System based on Deep Learning: A Multivariate Weather Forecasting Approach
by Md Zubair, Md. Shahidul Salim, Mehrab Mustafy Rahman, Mohammad Jahid Ibna Basher, Shahin Imran, Iqbal H. Sarker
First submitted to arxiv on: 21 Jan 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a context-based crop recommendation system powered by a weather forecast model to help farmers make informed decisions in Bangladesh’s challenging agricultural environment. The system utilizes a multivariate Stacked Bi-LSTM (three Bi-LSTM layers with a time Distributed layer) Network, which outperforms state-of-the-art LSTM models with an average R-Squared value of 0.9824. This weather forecasting model can predict Rainfall, Temperature, Humidity, and Sunshine for any given location in Bangladesh. The system not only provides viable farming decisions but also alerts farmers about extreme weather conditions to take preventive measures. Furthermore, the system makes knowledge-based crop suggestions for flood- and drought-prone regions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Agriculture is crucial for food security worldwide. However, unpredictable weather conditions like heavy rainfall, low temperatures, and droughts pose significant risks to global food production. To address this challenge, scientists have developed a new way to help farmers make informed decisions using a special computer model that predicts the weather. This model is very accurate and can predict rainfall, temperature, humidity, and sunshine for any location in Bangladesh. The system not only suggests the best crops to grow but also warns farmers about extreme weather conditions so they can take precautions to protect their crops. |
Keywords
* Artificial intelligence * Lstm * Temperature
