Publicação
Mathematical statistics vs machine learning: towards an intelligent modeling framework for soil and plant growth processes
| Resumo: | The work described in this dissertation focuses on the methods for analyzing MS and ML that are used in PF. The purpose of the work is to investigate these methods on their practical application to a specific set of data. In the course of the work, the following tasks were completed: the current state of affairs in the field of PF was investigated, the theoretical foundations of the methods of MS and ML were investigated, which were subjected to practical tests on a specific set of data. Conclusions were drawn about the advantages and disadvantages of these methods. A selection of works of scientists engaged in research on the introduction of a specific set of nutrients into the soil was also investigated. The most important contributions to this work are the practical application of various methods of analysis, as well as the design of a DST designed to help farmers integrate PF into their pilot training farms. |
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| Autores principais: | Labintseva, Valentina |
| Assunto: | Mathematical statistics Machine learning Linear regression lusterinG Precision farming Intelligent farming Modeling Soil PlantS Nutrients Moisture Decision support tool |
| Ano: | 2020 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| Resumo: | The work described in this dissertation focuses on the methods for analyzing MS and ML that are used in PF. The purpose of the work is to investigate these methods on their practical application to a specific set of data. In the course of the work, the following tasks were completed: the current state of affairs in the field of PF was investigated, the theoretical foundations of the methods of MS and ML were investigated, which were subjected to practical tests on a specific set of data. Conclusions were drawn about the advantages and disadvantages of these methods. A selection of works of scientists engaged in research on the introduction of a specific set of nutrients into the soil was also investigated. The most important contributions to this work are the practical application of various methods of analysis, as well as the design of a DST designed to help farmers integrate PF into their pilot training farms. |
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