Selection of clean technology options requires systematic evaluation based on multiple criteria which are often conflicting. The optimal choice should consider not just technical performance but also the economic, environmental and social aspects of technologies. Furthermore, the interdependencies of these aspects should also be considered. The decision-maker often needs to make explicit trade-offs while ranking the alternatives. In addition, data gaps and imprecise information that are typical when dealing with emerging technologies make conventional methods ineffective. This work thus proposes a Stochastic Fuzzy Analytic Hierarchical Network Process decision model to address the complexity and uncertainty involved in the clean technology selection process. This method first decomposes the problem into a hierarchical network structure, and then derives the probability distribution of the priority weights needed for ranking. The capabilities of the methodology are demonstrated with three case studies, involving the comparison of different carbon nanotube synthesis methods, nutrient removal treatment technology options for municipal wastewater, and low-carbon electricity sources in the Philippines.

清洁技术选择的选择需要基于经常相互冲突的多个标准进行系统评估。最佳选择不仅应考虑技术性能，还应考虑技术的经济，环境和社会方面。此外，还应考虑这些方面的相互依赖性。决策者经常需要在权衡替代方案时做出明确的权衡。另外，在处理新兴技术时，典型的数据空白和不精确的信息使传统方法无效。因此，这项工作提出了一种随机模糊分析层次网络过程决策模型，以解决清洁技术选择过程中涉及的复杂性和不确定性。此方法首先将问题分解为分层的网络结构，然后得出排序所需的优先权重的概率分布。通过三个案例研究证明了该方法的功能，其中涉及比较不同的碳纳米管合成方法，市政废水的营养去除处理技术选择以及菲律宾的低碳电源。