## 6 Conclusions  
The use of fuzzy neural network models is feasible for detecting existing meteorological aspects in data collected through meteorological stations. This streamlines the joining of techniques from different sectors of science for the benefit of the population of the state of Minas Gerais. Thus, it is expected that, with the knowledge acquired in this scientific work, the control and monitoring of aspects related to rainfall and temperatures in the state become a factor in the planning of people and government of the state of Minas Gerais. As the economy and social welfare depend on a balance of the two factors analyzed, new technologies are expected to be incorporated to improve control and tracking of weather stations, thus enabling citizens to receive predictive information to prevent or control certain behaviors that harm the environment. The rules obtained by the intelligent system are entirely based on the nature of the data present in the routine of state residents. As it was visualized that the climatic characteristics are changing over time, it is expected that, in the future, these impacts will be more substantial, mainly with an increase of average temperatures and a decrease of the rainfall indices. Managers and the public need to prepare for such impacts while seeking ways to mitigate the impacts on industry and people's daily lives. After validating the fuzzy rules obtained in the paper by professionals in the field, they can be used for the construction of expert systems to predict weather factors. Future work can investigate weather forecasting factor acknowledgments with missing data, using algorithms capable of controlling them in the assessment. Other hybrid models, neural networks models, feature selection techniques, and resampling missing data can be leveraged for pertinent extensions of this paper. Conceptualization, P.V.d.C.S. and L.B.d.O. ; methodology, L.A.F.d.N.J. ; software, P.V.d.C.S. and L.A.F.d.N.J. ; validation, L.B.d.O. and L.A.F.d.N.J. ; formal analysis, P.V.d.C.S. ; investigation, L.B.d.O. ; resources, P.V.d.C.S. ; data curation, P.V.d.C.S. and L.A.F.d.N.J. ; writing--original draft preparation, P.V.d.C.S. and L.B.d.O. ; writing--review and editing, P.V.d.C.S. and L.B.d.O. ; visualization, L.A.F.d.N.J. ; supervision, P.V.d.C.S. ; project administration, P.V.d.C.S. ; and funding acquisition, P.V.d.C.S. and L.A.F.d.N.J. This research received no external funding. The authors acknowledge the Faculty Una of Betim and the Federal Center of Technological Education of Minas Gerais--CEFET-MG. The authors declare no conflict of interest. The following abbreviations are used in this manuscript:  
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