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Fuzzy logic based heating systems operation scenario selection

机译:基于模糊逻辑的供热系统运行方案选择

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“Intelligent self-controlled heating system” have widely established their position as a research field during the last decade. The selection of methods to control performance of self-learning heating systems depends on a great number of conditions of the system being researched. Intelligent systems allow developing different scenarios of functioning of the investigated systems. Use of Fuzzy logic in self-learning systems may be used for tackling a wide range of system control and maintain problems (design and analysis of operation scenario and structure, monitor data base management, balancing of production capacities, optimization of heating system rules etc.). This research helps to detect the most problematics scenarios of operation rules selection process, check the efficiency of the decisions taken to select the work strategy and proposes to use a context sensitive and proactive fuzzy logical system for managing intelligent heating systems adaption to specific user.
机译:在过去的十年中,“智能自控加热系统”已广泛确立了其作为研究领域的地位。控制自学习加热系统性能的方法的选择取决于正在研究的系统的许多条件。智能系统允许开发被调查系统功能的不同方案。在自学习系统中使用模糊逻辑可用于解决各种系统控制和维护问题(操作方案和结构的设计和分析,监视数据库管理,生产能力的平衡,加热系统规则的优化等)。 )。这项研究有助于发现操作规则选择过程中最棘手的情况,检查选择工作策略的决策的效率,并建议使用上下文敏感和主动的模糊逻辑系统来管理针对特定用户的智能供暖系统。

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