Crop prediction using fuzzy logic / Muhamad Faisal Kamal
Agriculture is the art and science of soil planting, crop production, and livestock rearing. It involves preparing plant and animal products that can be used and sold to markets by humans. The development of agricultrue has led to the rise of civilizations for centuries. Before agriculture was wides...
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| التنسيق: | أطروحة |
| اللغة: | English |
| منشور في: |
2021
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| الوصول للمادة أونلاين: | https://ir.uitm.edu.my/id/eprint/55147/1/55147.pdf |
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my-uitm-ir.551472022-01-23T08:23:17Z Crop prediction using fuzzy logic / Muhamad Faisal Kamal 2021-02 Kamal, Muhamad Faisal QA Mathematics Multivariate analysis. Cluster analysis. Longitudinal method Analytic mechanics Agriculture is the art and science of soil planting, crop production, and livestock rearing. It involves preparing plant and animal products that can be used and sold to markets by humans. The development of agricultrue has led to the rise of civilizations for centuries. Before agriculture was widespread, people spent most of their time searcliuig for food, limiting wild animals, and collectmg wild plants. Approximately 11,000 years ago people slowly learned how to grow cereals and root crops, and settled down to a farm-based life. The mam factor for agriculture to succeed depends on the choice of the right crop and fertilizer for the soil. When choosing a suitable crop for the soil, the soil type and soil nutrients are of primary importance. Therefore, a prediction model must be built to help fanners make their choices (Anushiya et al., 2020). Today, major agricultural companies are investing in technology. This helps them to learn about crop production information, easier soil mapping by using GPS, fertilizer use by sensing technology, and weather information, all influenced by soil nutrient content. This knowledge will allow farmers to know the most productive crops in then region. Upon understanding the present soil state, this study also recommended which crops are most appropriate for planting based on a fuzzy logic model for crop recommendations (Martinez-Ojeda et al., 2019). 2021-02 Thesis https://ir.uitm.edu.my/id/eprint/55147/ https://ir.uitm.edu.my/id/eprint/55147/1/55147.pdf text en public degree Universiti Teknologi MARA, Terengganu Faculty of Computer and Mathematical Sciences |
| institution |
Universiti Teknologi MARA |
| collection |
UiTM Institutional Repository |
| language |
English |
| topic |
QA Mathematics QA Mathematics Analytic mechanics |
| spellingShingle |
QA Mathematics QA Mathematics Analytic mechanics Kamal, Muhamad Faisal Crop prediction using fuzzy logic / Muhamad Faisal Kamal |
| description |
Agriculture is the art and science of soil planting, crop production, and livestock rearing. It involves preparing plant and animal products that can be used and sold to markets by humans. The development of agricultrue has led to the rise of civilizations for centuries. Before agriculture was widespread, people spent most of their time searcliuig for food, limiting wild animals, and collectmg wild plants. Approximately 11,000 years ago people slowly learned how to grow cereals and root crops, and settled down to a farm-based life.
The mam factor for agriculture to succeed depends on the choice of the right crop and fertilizer for the soil. When choosing a suitable crop for the soil, the soil type and soil nutrients are of primary importance. Therefore, a prediction model must be built to help fanners make their choices (Anushiya et al., 2020).
Today, major agricultural companies are investing in technology. This helps them to learn about crop production information, easier soil mapping by using GPS, fertilizer use by sensing technology, and weather information, all influenced by soil nutrient content. This knowledge will allow farmers to know the most productive crops in then region. Upon understanding the present soil state, this study also recommended which crops are most appropriate for planting based on a fuzzy logic model for crop recommendations (Martinez-Ojeda et al., 2019). |
| format |
Thesis |
| qualification_level |
Bachelor degree |
| author |
Kamal, Muhamad Faisal |
| author_facet |
Kamal, Muhamad Faisal |
| author_sort |
Kamal, Muhamad Faisal |
| title |
Crop prediction using fuzzy logic / Muhamad Faisal Kamal |
| title_short |
Crop prediction using fuzzy logic / Muhamad Faisal Kamal |
| title_full |
Crop prediction using fuzzy logic / Muhamad Faisal Kamal |
| title_fullStr |
Crop prediction using fuzzy logic / Muhamad Faisal Kamal |
| title_full_unstemmed |
Crop prediction using fuzzy logic / Muhamad Faisal Kamal |
| title_sort |
crop prediction using fuzzy logic / muhamad faisal kamal |
| granting_institution |
Universiti Teknologi MARA, Terengganu |
| granting_department |
Faculty of Computer and Mathematical Sciences |
| publishDate |
2021 |
| url |
https://ir.uitm.edu.my/id/eprint/55147/1/55147.pdf |
| _version_ |
1783734905085100032 |