Sustainability Evaluation of Renewable Energy Incubators Using Interval Type-II Fuzzy AHP-TOPSIS with MEA-MLSSVM

With the development of renewable energy, energy incubators have emerged continuously. However, these present a crude model low-level replication and large-scale expansion, which has triggered series urgent problems including unbalanced regional development, low incubation efficiency, resource utilization, vicious competition for resources. There are huge challenges sustainable in future. A scientific accurate evaluation approach is great significance improving sustainability incubators. Therefore, this paper proposes novel method combining an interval type-II fuzzy analytic hierarchy process (AHP) with mind evolutionary algorithm-modified least-squares support vector machine (MEA-MLSSVM). The indicator system established from two aspects: service capability operational efficiency. TOPSIS integrated AHP employed index weighting assessment. In (LSSVM), traditional radial basis function replaced wavelet transform (WT), parameters fine-tuned by algorithm (MEA). Accordingly, establishment comprehensive accomplished paper. experimental study reveals that technique advantages scientificity precision provides decision-making to realize operation.