Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Artificial neural network models for indoor temperature prediction: investigations in two buildings
Neural Computing and Applications
Obtaining transparent models of chaotic systems with multi-objective simulated annealing algorithms
Information Sciences: an International Journal
Minimizing Energy Consumption in Heating Systems under Uncertainty
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
A fuzzy logic based efficient energy saving approach for domestic heating systems
Integrated Computer-Aided Engineering
Distributed monitoring and control of office buildings by embedded agents
Information Sciences: an International Journal
Energy saving by means of fuzzy systems
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Modelling of heat flux in building using soft-computing techniques
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
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A local Spanish company that produces electric heaters needs an energy saving device to be integrated with the heaters. It was proven that a hybrid artificial intelligent systems (HAIS) could afford the energy saving reasonably, even though some improvements must be introduced. One of the critical elements in the process of designing an energy saving system is the thermodynamical modeling of the house to be controlled. This work presents a study of different first order techniques, some taken from the literature and other new proposals, for the prediction of the thermal dynamics in a house. Finally it is concluded that a first order prediction system is not a valid prediction model for such an energy saving system.