Development of wind energy in the agricultural sector of Iran and investment priorities of the decision maker groups using artificial intelligence-based quantum hybrid picture fuzzy rough modelling

Abstract

The main purpose of this study is to make evaluations for the indicators of wind energy investments in Iranian agricultural sector. For this purpose, a novel model is constructed that has three different stages. Firstly, expert choices are prioritized with artificial intelligence-based decision-making model. Secondly, performance indicators of the wind energy projects in the agricultural industry are weighted via quantum picture fuzzy rough sets-based M-SWARA. Thirdly, investment priority alternatives are ranked by considering the quantum picture fuzzy rough sets based VIKOR technique. The main contribution of this study is that artificial intelligence methodology is integrated with the fuzzy decision-making analysis. With the help of this analysis, experts can be prioritized according to their qualifications. According to the weighting results, it is identified that regulations play a crucial role for each group. On the other side, the ranking results indicate that storage solutions play the most crucial role for the improvements of the wind energy projects for Iranian agriculture industry.