Programa de Pós-Graduação em Gestão de Riscos e Desastres Naturais na Amazônia - PPGGRD/IG
URI Permanente desta comunidadehttps://repositorio.ufpa.br/handle/2011/9943
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Dissertação Acesso aberto (Open Access) Sistema hidrológico para previsão de risco na Amazônia utilizando redes neurais.(Universidade Federal do Pará, 2019-03-02) PERES, Victor da Cruz; ROCHA, Edson José Paulino da; http://lattes.cnpq.br/2313369423727020The estimation of the future behavior of the levels of a river basin is fundamental for the elaboration of the plan of management of its water resources. The objective of this research was to model the relationship between rainfall and level through a technique known as artificial neural networks (RNA). RNAs are empirical models with functions similar to the functioning of the human brain. In this research, the ability of RNA to model the rain-level process on a daily basis was evaluated. Influences of network architecture, initialization of weights, and extension of data series were considered during RNA training. The five RNAs that produced the best results were confronted with the observed results. The results were very satisfactory. Finding in a dry and full alert system in Itaituba-Pa.Dissertação Acesso aberto (Open Access) Sistema regional de monitoramento de seca.(Universidade Federal do Pará, 2019-02-01) PEDROSA, João Paulo da Costa; MORAES, Bergson Cavalcanti de; http://lattes.cnpq.br/8462634544908052Drought is a natural phenomenon of meteorological origin, due to a precipitation deficit, which is verified every year in different regions of the globe, being therefore a recurring feature of the climate and not a rare occurrence. A drought situation can result in a natural disaster if there is no local resilience as a capacity for managing water resources to minimize their adverse effects. In many regions, as in developing countries, the consequences of droughts reach such a magnitude that they are often classified as catastrophic, causing famine, deaths and population exoduses. Considering this problem, the present study adapted a physical-mathematical model for the local conditions able to monitor drought based on the Palmer Drought Severity Index (ISSP) through changes in latitude, field capacity, water balance of Thornthwaite and the data of the files needed to calculate the index. The model used precipitation and air temperature data from 1987 to 2014. The model also had to be compiled for the C ++ language. We obtained as an answer an index with better reliability by the fact of using data with high resolution and more representative for the Amazon region.