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A general type-2 Fuzzy Logic based Multi-Criteria group decision making for lighting level selection in an intelligent environment

机译:一种智能环境中照明级别选择的一般类型-2模糊逻辑的多标准组决策

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Selecting a suitable lighting level for reading is crucial to the overall success of reading comprehension. The light level preferences vary amongst the various users specifically according to changing environment conditions. Thus, it is important when designing the illumination at various intelligent shared spaces to consider the preferences of users from different backgrounds. Hence, we propose a Fuzzy Logic-Multi Criteria Group Decision Making (FL-MCGDM) system which provides a comprehensive valuation from a group of decision makers utilizes General Type-2 Fuzzy Sets. We have carried out experiments in the intelligent apartment (iSpace) located in the University of Essex. The aggregation operation in the proposed method aggregates the various DMs opinions which allow handling the disagreements of DMs' opinions into a unique approval. In addition, the proposed system showed agreement between the proposed method and the real decision outputs from DMs (as quantified by the Pearson Correlation) which outperformed the FL-MCGDM systems based on Type-1 Fuzzy Sets, Interval Type-2 Fuzzy Sets and Interval Type-2 Fuzzy Sets with Hesitation Index.
机译:选择读合适的照明水平是阅读理解的整体成功至关重要。光级的偏好特别根据变化的环境条件的各种用户之间的不同而不同。因此,设计在各种智能共享空间的照明考虑来自不同背景的用户的偏好时是重要的。因此,我们提出了一个模糊的多准则群决策中(FL-MCGDM)系统,该系统由一组决策者提供了一个全面的评估一般采用2型模糊集。我们已经在位于埃塞克斯大学智能公寓(iSpace的)进行了实验。在该方法的聚合操作聚合了各种对话管理的意见,允许处理的对话管理的意见分歧成一个独特的批准。此外,所提出的系统显示出所提出的方法,并从DMS上真正决定输出(如通过皮尔逊相关量化)之间的协议,其优于基于所述FL-MCGDM系统1型模糊集,区间2型模糊集与区间类型2犹豫指标的模糊集。

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