Proposing Suitable Plant Species Using MLP Combined with Sliding WINDOWS
Vo Khuong Duy, Bui Thi Diem Trinh, Tran Ngoc Truc Linh, Ngo Ho Anh Khoi
Abstract: Currently, the field of science and technology, particularly Artificial Intelligence (AI), is undergoing significant development. Artificial Intelligence involves computer-based emulation of human intelligence. Machine learning, a subset of AI, employs mathematical methods to enhance computational performance. The application of AI in agriculture is creating opportunities to optimize the selection of suitable plant species, thereby contributing to increased income for farmers and economic development. By applying machine learning techniques to the "Agricultural Crop Dataset," the project has developed an efficient system for predicting appropriate plant species for farmers, driving the practical application of AI in agriculture and establishing a foundation for sustainable economic growth.
Keyword: Machine Learning, AI, sliding windows, plant species, MLP.
Agricultural Attributes
| Name | Description |
|---|---|
| N (Nitrogen) | Essential nutrient for plant growth and protein synthesis |
| P (Phosphorus) | Component of DNA and RNA, vital for plant structure and seed yield |
| K (Potassium) | Enhances plant resilience to adverse conditions and promotes growth |
| Ph (Soil pH) | Measure of soil acidity or alkalinity, crucial for nutrient availability |
| Rainfall | Amount of precipitation affecting soil moisture and plant water supply |
| Temperature | Environmental temperature impacting plant growth and development |
| Humidity | Amount of water vapor in the air influencing plant gas exchange and water absorption |
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