Predicting the distribution of thermal comfort votes

Anika Schumann; Nic Wilson

doi:10.1007/978-3-642-21827-9_49

Predicting the distribution of thermal comfort votes

Anika Schumann
, Nic Wilson

IBM

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

Abstract

Maximizing occupant comfort and minimizing energy costs are two challenging tasks in the efficient operation of any office building. Often these objectives cannot be achieved simultaneously which asks for methods that resolve this trade-off in the best way. Several approaches deal with this problem by focusing on optimizing one of the above criteria while keeping the other one within an acceptable range. However, defining the latter can be very difficult in practice. In particular, setting the acceptable comfort range for offices shared by multiple occupants with conflicting thermal comfort preferences is a challenging problem. This paper presents an intelligent decision support system that assists a building operator in resolving the trade-off between energy efficiency and occupant comfort. Its key component is a case-based reasoning algorithm for predicting the distribution of the occupants' thermal preferences.

Original language	English
Title of host publication	Modern Approaches in Applied Intelligence - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Proceedings
Pages	480-489
Number of pages	10
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-21827-9_49
Publication status	Published - 2011
Event	24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011 - Syracuse, NY, United States Duration: 28 Jun 2011 → 1 Jul 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	6704 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011
Country/Territory	United States
City	Syracuse, NY
Period	28/06/11 → 1/07/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

decision support systems
intelligent systems
thermal comfort

Access to Document

10.1007/978-3-642-21827-9_49

Cite this

Schumann, A., & Wilson, N. (2011). Predicting the distribution of thermal comfort votes. In Modern Approaches in Applied Intelligence - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Proceedings (PART 2 ed., pp. 480-489). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6704 LNAI, No. PART 2). https://doi.org/10.1007/978-3-642-21827-9_49

Schumann, Anika ; Wilson, Nic. / Predicting the distribution of thermal comfort votes. Modern Approaches in Applied Intelligence - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Proceedings. PART 2. ed. 2011. pp. 480-489 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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title = "Predicting the distribution of thermal comfort votes",

abstract = "Maximizing occupant comfort and minimizing energy costs are two challenging tasks in the efficient operation of any office building. Often these objectives cannot be achieved simultaneously which asks for methods that resolve this trade-off in the best way. Several approaches deal with this problem by focusing on optimizing one of the above criteria while keeping the other one within an acceptable range. However, defining the latter can be very difficult in practice. In particular, setting the acceptable comfort range for offices shared by multiple occupants with conflicting thermal comfort preferences is a challenging problem. This paper presents an intelligent decision support system that assists a building operator in resolving the trade-off between energy efficiency and occupant comfort. Its key component is a case-based reasoning algorithm for predicting the distribution of the occupants' thermal preferences.",

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Schumann, A & Wilson, N 2011, Predicting the distribution of thermal comfort votes. in Modern Approaches in Applied Intelligence - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 6704 LNAI, pp. 480-489, 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Syracuse, NY, United States, 28/06/11. https://doi.org/10.1007/978-3-642-21827-9_49

Predicting the distribution of thermal comfort votes. / Schumann, Anika; Wilson, Nic.
Modern Approaches in Applied Intelligence - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Proceedings. PART 2. ed. 2011. p. 480-489 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6704 LNAI, No. PART 2).

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

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AU - Wilson, Nic

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Schumann A, Wilson N. Predicting the distribution of thermal comfort votes. In Modern Approaches in Applied Intelligence - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Proceedings. PART 2 ed. 2011. p. 480-489. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-21827-9_49

Predicting the distribution of thermal comfort votes

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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