Estrutura de referência para integração entre avaliação do ciclo de vida e aprendizado de máquina
DOI:
https://doi.org/10.46421/entac.v20i1.5992Palavras-chave:
Modelo integrativo, Predição, Otimização, ClusterizaçãoResumo
Esta pesquisa identifica estudos que associam Avaliação do Ciclo de Vida (ACV) e o aprendizado de máquinas (AP) e elabora uma estrutura de referência de integração entre essas áreas. Para tal, o método estruturalista foi aplicado com o seguinte delineamento: identificação dos elementos para integração a partir de uma Revisão Sistemática de Literatura (RSL), conceituação, estabelecimento das relações entre os elementos, elaboração do modelo estrutural e análise. A estrutura integrativa categoriza e associa elementos característicos da ACV e do AP. O estudo confirmou as etapas da ACV como as categorias de seus elementos, sendo estas: goal and scope definition, life cycle inventory, life cycle impact assessment e interpretation; e relacionada à AP: algorithm. Foi possível verificar que AP auxilia em todos os estágios da ACV, mas recursos como predição, otimização e clusterização variam a depender da etapa e objetivos. A contribuição da estrutura integrativa está no auxílio aos profissionais de ACV na seleção dos diferentes recursos do AP incorporando a inteligência artificial para os diferentes cenários de avaliação de impacto ambiental.
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