Towards a Cognitive Agent-based Model for Air Conditioners Purchasing Prediction
Author(s) -
Nataliya Mogles,
Alfonso P. Ramallo-González,
Elizabeth Gabe-Thomas
Publication year - 2015
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2015.05.270
Subject(s) - air conditioning , overheating (electricity) , purchasing , computer science , penetration (warfare) , air temperature , environmental science , environmental economics , operations research , meteorology , economics , operations management , mechanical engineering , physics , quantum mechanics , engineering
Climate change as a result of human activities is a problem of a paramount importance. The global temperature on Earth is gradually increasing and it may lead to substantially hotter summers in a moderate belt of Europe, which in turn is likely to influence the air conditioning penetration in this region. The current work is an attempt to predict air conditioning penetration in different residential areas in the UK between 2030-2090 using an integration of calibrated building models, future weather predictions and an agent-based model. Simulation results suggest that up to 12% of homes would install an air conditioner in 75 years’ time assuming an average purchasing ability of the households. The performed simulations provide more insight into the influence of overheating intensity along with households’ purchasing ability and social norms upon households’ decisions to purchase an air conditioner
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