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Predicción del riesgo de robo: enfoque bayesiano de modelización espacio - temporal y caso de estudio.
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| dc.contributor | Roa, Heydi Mariana ,Director | |
| dc.contributor.author | Rodríguez Méndez, Claudia Paola | |
| dc.contributor.author | Ortiz Santamaria, Samantha Melissa | |
| dc.date | 2022 | |
| dc.date.accessioned | 2023-01-16T16:43:17Z | |
| dc.date.available | 2023-01-16T16:43:17Z | |
| dc.date.created | Rodríguez Méndez, Claudia Paola | |
| dc.date.created | Ortiz Santamaria, Samantha Melissa | |
| dc.date.issued | 2022 | |
| dc.identifier.citation | Rodríguez Méndez, C.; Ortiz Santamaria, S.(2022). Predicción del riesgo de robo: enfoque bayesiano de modelización espacio - temporal y caso de estudio.[Proyecto Integrador Escuela Superior Politécnica del Litoral]. Repositorio Institucional ESPOL. dspace.espol.edu.ec Cita de tesis según Normas APA 7ª | es_EC |
| dc.identifier.uri | http://www.dspace.espol.edu.ec/handle/123456789/56598 | |
| dc.description.abstract | La seguridad de los ecuatorianos se ha visto afectada por diversos factores y el querer proteger a nuestros seres queridos ha sido uno de los objetivos personales más comunes en todo el mundo, sobre todo salvaguardar nuestras pertenencias y más aún nuestras vidas. Guayaquil siendo una de las ciudades más grandes del Ecuador, llena de comercios, grandes empresas, luces en todo momento. Una ciudad que alberga muchos ecuatorianos y cientos de turistas a diario se ha convertido en un foco de alertas de robo que aumenta con el pasar del tiempo sin contar el retroceso de la economía que se vio involucrada por una de las pandemias más impactantes en la historia de la humanidad, el Covid -19. Por tal motivo, este proyecto busca diseñar un modelo espacio - temporal para la predicción del riesgo de robo en la ciudad de Guayaquil, mediante la aplicación de la metodología bayesiana, en conjunto ala lenguaje de programación R, utilizando como unidad de medida a los barrios de la ciudad. Los datos utilizados para la construcción del modelo fueron obtenidos desde las bases de datos del Servicio de Seguridad Integrado ECU911. | es_EC |
| dc.language | 2022 | |
| dc.language.iso | esp | es_EC |
| dc.publisher | ESPOL. FCNM | es_EC |
| dc.rights | openAccess | |
| dc.subject | Riesgo | es_EC |
| dc.subject | Robo | es_EC |
| dc.subject | Seguridad | es_EC |
| dc.subject | Espacio - tiempo | es_EC |
| dc.subject | Metodología bayesiano | es_EC |
| dc.title | Predicción del riesgo de robo: enfoque bayesiano de modelización espacio - temporal y caso de estudio. | es_EC |
| dc.type | Thesis proyecto integrador | es_EC |
| dc.description.abstractenglish | The security of Ecuadorians has been affected by various factors and wanting to protect our loved ones has been one of the most common personal objectives throughout the world, especially safeguarding our belongings and even more so our lives. Guayaquil being one of the largest cities in Ecuador, full of shops, large companies, lights at all times. A city that is home to many Ecuadorians and hundreds of tourists daily has become a focus of robbery alerts that increase over time without counting the setback of the economy that was involved in one of the most shocking pandemics in history. of humanity, Covid-19. For this reason, this project seeks to design a space-time model for predicting the risk of theft in the city of Guayaquil, through the application of the Bayesian methodology, together with the programming language R, using neighborhoods as a unit of measure. of the city. The data used for the construction of the model was obtained from the databases of the Integrated Security Service ECU911. The data of the other variables included for the study, such as rainfall, which indicates whether it was a rainy day or not, the population of each of the neighborhoods of Guayaquil, were obtained from INEC and INOCAR pages, while the data of geolocation of the UPC Community Police Units, from OpenStreetMap. Achieving the estimation of the robbery risk for each of the neighborhoods, with a higher estimate due to the influence of the joint space-time effect. It was also found that the precipitation variable, which was considered instead of the dichotomous variable State of rain, due to the lack of official historical data on the occurrence of rain during the periods analyzed, does not generate contributions within the model, but on the contrary the UPC variable does represent a strong influence on the risk of theft, due to its geographical presence in the neighborhoods. iii Finally, with the applied model it is possible to identify the neighborhoods with the highest number of robbery alerts, which are categorized as hot spots, also providing information for timely management by the competent authorities for a better execution of resources and guarantee of citizen security. Keywords: risk, theft, security, model, space-time, Bayesian |
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Tesis de Estadística
Estadística