Orr, S; (2018) Data fusion to synthesise quantitative evidence, value and socio-economic factors: A framework and example of Dempster-Shafer theory. In: Broström, T and Nilsen, L and Carlsten, S, (eds.) Conference Report: The 3rd International Conference on Energy Efficiency in Historic Buildings. (pp. pp. 163-171). Uppsala University: Uppsala, Sweden.

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Abstract

This paper presents a framework and example of how fuzzy data fusion processes can support decision making for energy efficiency in historic buildings. Dempster-Shafer (DS) theory is a framework of reasoning that deals with uncertainty, allowing one to combine evidence from different sources. DS theory can handle conflicting information, with the aim to provide a representation of the appropriateness and uncertainty for each option. The theory starts with a set of possibilities: for example, a range of retrofit options or energy-use schemes. Each one is assigned a degree of belief depending on how many evidence inputs contains the proposition and the subjective probability. DS theory incorporates hard data, e.g. energy models and economic estimates, and opinion, e.g. disruption to activities and changes in aesthetics. It is proposed that DS Theory and hard-soft data fusion algorithms provide an approach that can incorporate value and socio-economic aspects into decision making.

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