A remote sensing satellite observation scheme evaluation method based on granular computing of intuitionistic linguistic preference relation

With the sustainable development of remote sensing satellite observation technology, the effectiveness of the remote sensing satellite observation scheme has drawn wide attention in recent years. A suitable evaluation model can provide a credible improvement basis and guide observation technology's continuous development. In this study, we present an original method based on granular computing to evaluate the remote sensing satellite observation schemes by employing intuitionistic linguistic preference relation, which is ideal for allowing evaluation team members to depict their actual opinions. The granulation of the intuitionistic linguistic preference relation is regarded as an optimization problem, solved by using the particle swarm optimization. The optimization criterion comprised of consensus and consistency is maximized by a suitable mapping of the intuitionistic linguistic preference relation on information granules. Once the granulation of the intuitionistic linguistic preference relation is completed, the solution to the evaluation problem is constructed by the selection process in virtue of the dominance levels of observation schemes and the prioritization relationship of evaluation team members. Finally, an experimental example about the evaluation of remote sensing satellite observation schemes is reported to support the feasibility and practicality of the proposed evaluation method. Furthermore, comparative analysis with other methods is also analyzed to further demonstrate the performance of the designed method.