Development of artificial intelligence models for the enrichment and exploitation of geospatial data in the built environment
Geospatial data treatment is an important task since it is a big part of big data. Nowadays, geospatial data exploitation is lacking in terms of artificial intelligence. In this work, we focus on the usage of a machine learning models to exploit geospatial data. We will follow a complete workflow fr...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad del País Vasco |
| Repositorio: | Addi. Archivo Digital para la Docencia y la Investigación |
| OAI Identifier: | oai:addi.ehu.eus:10810/58973 |
| Acceso en línea: | http://hdl.handle.net/10810/58973 |
| Access Level: | acceso abierto |
| Palabra clave: | geospatial data georeferenced infrastructure civil work prediction |
| Sumario: | Geospatial data treatment is an important task since it is a big part of big data. Nowadays, geospatial data exploitation is lacking in terms of artificial intelligence. In this work, we focus on the usage of a machine learning models to exploit geospatial data. We will follow a complete workflow from the collection and first descriptive analysis of the data to the development and evaluation of the different machine learning algorithms. From download dataset we will predict if the download will lead to civil work, in other words, it is a classification problem. We conclude that combining machine learning and geospatial data we can get a lot out of it. |
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