Fuzzy Rules to Help Predict Rains and Temperatures in a Brazilian Capital State Based on Data Collected from Satellites
Source abstract
Abstract
The forecast for rainfall and temperatures in underdevelope countries can help in the definition of public and private investment strategies in preventive and corrective nature. Water is an essential element for the economy and living things. This study had a main objective to use an intelligent hybrid model capable of extracting fuzzy rules from a historical series of temperatures and rainfall indices of the state of Minas Gerais in Brazil, more specifically in the capital. Because this is state has several rivers fundamental to the Brazilian economy, this study intended to find knowledge in the data of the problem to help public managers and private investors to act dynamically in the prediction of future temperatures and how they can interfere in the decisions related to the population of the state. The results confirm that the intelligent hybrid model can act with efficiency in the generation of predictions about the temperatures and average rainfall indices, being an efficient tool to predict the water situation in the future of this critical state for Brazil.
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Research context
OpenAlex topics: Hydrological Forecasting Using AI · Water Quality Monitoring Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Federal Center of Technological Education of Minas Gerais-CEFET-MG-Information Governance Secretariat, Belo Horizonte 30421-169, Brazil
Faculty Una of Betim-Information Systems Course, Betim 32510-010, Brazil
Graduate Program in Electrical Engineering-Federal University of Minas Gerais-UFMG, Belo Horizonte 31270-901, Brazil
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