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En el instante 11 de octubre de 2025, 1:23:33 UTC,
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Añadido recurso Spatio-temporal interpolation of rainfall data in western Mexico a Spatio-temporal interpolation of rainfall data in western Mexico
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2 | "author": "ZCM Vargas, SI Valdez, J Paredes-Tavares", | 2 | "author": "ZCM Vargas, SI Valdez, J Paredes-Tavares", | ||
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19 | Observatorio Metropolitano CentroGeo. Incluye art\u00edculos | 19 | Observatorio Metropolitano CentroGeo. Incluye art\u00edculos | ||
20 | presentados en congresos nacionales e internacionales, manuscritos en | 20 | presentados en congresos nacionales e internacionales, manuscritos en | ||
21 | formato preprint, cap\u00edtulos de libro y trabajos publicados en | 21 | formato preprint, cap\u00edtulos de libro y trabajos publicados en | ||
22 | revistas cient\u00edficas especializadas. Estos materiales reflejan la | 22 | revistas cient\u00edficas especializadas. Estos materiales reflejan la | ||
23 | labor de investigaci\u00f3n, desarrollo metodol\u00f3gico y | 23 | labor de investigaci\u00f3n, desarrollo metodol\u00f3gico y | ||
24 | an\u00e1lisis territorial del observatorio, contribuyendo al avance | 24 | an\u00e1lisis territorial del observatorio, contribuyendo al avance | ||
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41 | "name": | 41 | "name": | ||
42 | mporal-interpolation-of-rainfall-data-in-western-mexico-a391f135ae0c", | 42 | mporal-interpolation-of-rainfall-data-in-western-mexico-a391f135ae0c", | ||
43 | "notes": "One of the most common problems related to meteorological | 43 | "notes": "One of the most common problems related to meteorological | ||
44 | information is the missing registers. This lack of data generates | 44 | information is the missing registers. This lack of data generates | ||
45 | uncertainties in the analysis of climate, hydrology, and natural | 45 | uncertainties in the analysis of climate, hydrology, and natural | ||
46 | disasters. In Mexico, very often, this problem is present in all the | 46 | disasters. In Mexico, very often, this problem is present in all the | ||
47 | meteorological stations of the country. In this study, we apply two | 47 | meteorological stations of the country. In this study, we apply two | ||
48 | well-established spatial interpolation methods that have report | 48 | well-established spatial interpolation methods that have report | ||
49 | competitive performance in the specialized literature: the Inverse | 49 | competitive performance in the specialized literature: the Inverse | ||
50 | Distance Weighting (IDW) and Modified Inverse Distance Weighting | 50 | Distance Weighting (IDW) and Modified Inverse Distance Weighting | ||
51 | (MIDW); and they are compared with a proposal of spatio-temporal | 51 | (MIDW); and they are compared with a proposal of spatio-temporal | ||
52 | regression using an artificial neural network of the kind of | 52 | regression using an artificial neural network of the kind of | ||
53 | multilayer perceptron (MLP). The results show that using a combination | 53 | multilayer perceptron (MLP). The results show that using a combination | ||
54 | of spatial and temporal data with a low number of predictors is | 54 | of spatial and temporal data with a low number of predictors is | ||
55 | competitive with the comparing methods using a high number of | 55 | competitive with the comparing methods using a high number of | ||
56 | predictors. We compare the methods through statistical measures of the | 56 | predictors. We compare the methods through statistical measures of the | ||
57 | error for 31 meteorological stations of the Jalisco state in the | 57 | error for 31 meteorological stations of the Jalisco state in the | ||
58 | period of 2002-2006.", | 58 | period of 2002-2006.", | ||
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88 | all the meteorological stations of the country. In this study, we | ||||
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90 | report competitive performance in the specialized literature: the | ||||
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180 | "title": "Spatio-temporal interpolation of rainfall data in western | 219 | "title": "Spatio-temporal interpolation of rainfall data in western | ||
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