Abstract
With the development of renewable energy, renewable energy incubators have emerged continuously. However, these incubators present a crude development model of low-level replication and large-scale expansion, which has triggered a series of urgent problems including unbalanced regional development, low incubation efficiency, low resource utilization, and vicious competition for resources. There are huge challenges for the sustainable development of incubators in the future. A scientific and accurate evaluation approach is of great significance for improving the sustainability of renewable energy incubators. Therefore, this paper proposes a 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 is established from two aspects: service capability and operational efficiency. TOPSIS integrated with an interval type-II fuzzy AHP is employed for index weighting and assessment. In the least-squares support vector machine (LSSVM), the traditional radial basis function is replaced with the wavelet transform function (WT), and the parameters are fine-tuned by the mind evolutionary algorithm (MEA). Accordingly, the establishment of a comprehensive sustainability evaluation model for renewable energy incubators is accomplished in this paper. The experimental study reveals that this novel technique has the advantages of scientificity and precision and provides a decision-making basis for renewable energy incubators to realize sustainable operation.
Highlights
The renewable energy incubator, as an efficacious tool of renewable energy achievement in industrialization, has aroused wide public concern
The specific steps are listed as follows: Step 4: Optimize the parameters in MLSSVM via mind evolutionary algorithm (MEA), which are related to evaluation precision of sustainable development for renewable energy incubators
In line with the ideas derived from 40 experts, test the consistency of the judgment matrix attain thethe linguistic scale in values twoMLSSVM
Summary
The renewable energy incubator, as an efficacious tool of renewable energy achievement in industrialization, has aroused wide public concern. It is a kind of business incubator, the concept of which came from the Betevia industrial center under the leadership of Mancuso in 1956 [1]. The role of small start-ups in economic growth has been generally accepted since 1980, and numerous business incubators have emerged and achieved success in developed countries such as Europe and America [2]. In order to describe the status, identify the bottleneck, and address the problems in sustainable growth, it is necessary to evaluate the sustainable development capacity of renewable energy incubators The sustainable development of incubators is faced with great challenges, due to their extensive growth, of low-level replication and large-scale expansion, which has caused a series of problems including unbalanced regional development, low incubation efficiency, low resource utilization rate, and vicious resource competition [4].
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