Data mining for time series and its applicat.ion in rainfall precipitations in the canton Huaca Ecuador area - Yandún Velasteguí , Marco Antonio; Montenegro Argoti, Carlos Fernando (SATHIRI, 2023)
In the San Pedro de Huaca canton there is the San Francisco Experimental Farm, it has a meteorological station that collects data related to the climate and among them also records of rainfall are obtained, with these data a minimum analysis is made including the data historical rainfall, I do not know has evidenced the use of data mining tools to determine rainfall or generate a forecast, the above is obtained through ancestral knowledge of farmers. With the use of the data stored by the meteorological station with its variables and units of measurement, the research was carried out that is based on the application of predictive data mining techniques applied the Cross Industry Standard Process for Data Mining CRISP-DM methodology, (Industry standard process for data mining), fulfilling all its phases. For the modeling stage, mobile forecasts are applied, for the forecast of time series, where it makes predictions with historical data in this case 2019 and 2020, to carry out all this process the programming language R was used since presents great advantages in data analysis, the results obtained correspond to the rainfall forecasts obtained for each month of the year 2021, the unit of measurement of these data is in millimeters per square meter, this information is displayed in a web application shinnyapp.io displaying and downloading the data analysis, publicly available.