Anthropogenic impact evaluation and material stream optimization by artificial intelligence

Abstract

To evaluate the anthropogenic impact of pollutants on the environment or material streams in the natural circle it is indispensable to use the benefits of computer systems – in particular artificial intelligence. Most of impact factors are time related and therefore difficult to calculate and to optimize in a natural environmental system. By using evolutionary algorithms as a part of the artificial intelligence to simulate, estimate and evaluate pollutants or specific materials it makes it possible to evaluate the impact on the environment and to optimize material streams in nature or recycling streams. Evolutionary algorithms are used in two different applications: optimizing recycling material streams and anthropogenic impact evaluation. To optimize recycling material streams, the production process as well as the quality of the products must be known. With knowledge of these requirements it is possible to use evolutionary algorithms for the optimization of recycling material streams. Similar to that is the evaluation of anthropogenic impacts. For this application different states of impact are determined and compared with anthropogenic uninfluenced situations. Because of plenty time related impact factors only the use of evolutionary algorithms shows effective evaluation results. The benefit of these applications is the fast and precise calculation of the local and global optima of the optimizing problem. This calculation method uses the benefits of the biological reproduction by applications of mutation, selection and recombination to find one of the best results in a huge amount of possible and potential results. For the use of recycling materials in the production process of new materials it could be proved that in spite of high quotes of recycling materials in different material classes, no quality was lost.