Índice de calidad del agua recolectada en el río Bogotá: un análisis mediante la computación cognitiva Watson
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Dec 1, 2017
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Abstract
En este artículo se analizan los datos sobre la calidad del agua del río Bogotá en el periodo 2008-2015 proporcionados por la Corporación Autónoma Regional de Cundinamarca (CAR); para ello se aplica la computación cognitiva, con el fn de establecer los cambios más signifcativos que se han presentado. Además, se hace un análisis espacio-tiempo para las variables relacionadasen el recurso hídrico en la cuenca alta, para así contribuir con un mecanismo que facilite la comprensión del comportamiento, a través del tiempo, del estado de la calidad del agua. Esto hará posible que las entidades territoriales tengan nuevos criterios y visiones a la hora de formular o reformular nuevos planes. Como herramienta de análisis se utiliza IBM Watson.Abstract This article analyzes the data on the water quality of the Bogotá river during the period 2008-2015, provided by the Autonomous Regional Corporation of Cundinamarca (CAR); For this purpose cognitive computation is applied, in order to establish the most signifcant changes that have been presented. In addition, a space-time analysis is performed of the related variables in the water resource in the upper basin, in order to contribute to a mechanism that facilitates the understanding of the behavior, over time, of the state of water quality. This will make it possible for territorial entities to have new criteria and visions when formulating or reformulating new plans. IBM Watson is used as an analysis tool.Resumo Este artigo analisa os dados da qualidade da água do rio Bogotá no período 2008-2015, fornecidos pela Corporação Regional Autônoma de Cundinamarca (CAR), na Colômbia; Para este fm, a computação cognitiva é aplicada, com o objetivo de estabelecer as mudanças mais signifcativas que têm se apresentado. Além disso, uma análise espaço-temporal foi realizada para as variáveis relacionadas no recurso hídrico na bacia superior, a fm de contribuir com um mecanismo que facilite a compreensão do comportamento do estado da qualidade da água, ao longo do tempo. Isso permitirá que as entidades territoriais tenham novos critérios e visões para formular ou reformular novos planos. Como uma ferramenta do análise, o IBM Watson foi usado.
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Barrera-Williams, C., Montenegro-Marín, C. E., & Gaona-García, P. A. (2017). Índice de calidad del agua recolectada en el río Bogotá: un análisis mediante la computación cognitiva Watson. Ingenio Magno, 8(1), 104-117. Retrieved from http://revistas.santototunja.edu.co/index.php/ingeniomagno/article/view/1392
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Artículos Vol. 8-1
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Lobbrecht, A. H., Dibike, Y. B. y Solomatine, D. P. (2002). Hydroinformatics applications of neural networks and fuzzy logic to integrated water management project report. Recueerado de https://www.researchgate.net/publication/268203104_Hydroinformatics_Applications_of_Neural_Networks_and_Fuzzy_Logic_to_Integrated_Water_Management_Project_Report
McCord, M. C. (1990). Slot grammar: A system for simpler construction of practical natural language grammars. En Natural Language and Logic: International Scientifc Symposium. Berlín: Srpinger-Verlag.
Miller, J. D. (2016). Learning IBM Watson Analytics: make the most advanced predictive analytical processes easy using Watson Analytics with this easy-to-follow practical guide. Birmingham: Packt Publ. Recuperado de http://cds.cern.ch/record/2152952
Ministerio de la Protección Social (2007). Decreto 1575 de 2007, por el cual se establece el Sistema para la Protección y Control de la Calidad del Agua para Consumo Humano. Recuperado de http://www.minambiente.
gov.co/images/normativa/decretos/2007/dec_1775_2007.pdf
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Roland, E., Uhrmacher, A. y Saha, K. (2009). Data mining for simulation algorithm selection. Recuperado de http://dl.acm.org/citation.cfm?id=1537633
Rosado, A. y Verjel, A. (2015). Minería de datos aplicada a la demanda del transporte aéreo en Ocaña, Norte de Santander. Tecnura, 19(45), 101-113.
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