Using Artificial Intelligence in energy efficient construction

Abstract

Artificial Neural Networks (ANNs), genetic algorithms, case based reasoning (CBR), and hybrid systems are all methods of artificial intelligence. This dissertation presents a literature overview and its author's achievements in methods of utilizing artificial intelligence methods in energy efficient buildings, which include: an expert system for supporting the financing of thermo-modernization investment, a method of optimizing thermo-modernization strategies for groups of buildings using genetic algorithms, and a case based reasoning system (CBR) intended to facilitate the design of energy efficient single family housing. Case based reasoning consists of comparing new problems with past problems and using a past solution. In the CBR system, previously developed single family housing designs will be described using linguistic variables defined as fuzzy sets. The designer, who wants to create the documentation for a new energy efficient building after talking with the investor about his or her expectations, enters a query, defined as linguistic variables, into the system. The system finds the documentation of already constructed buildings, most closely matching the investor's requirements. The designer performs the required adjustments, and after the investor's approval, places the new documentation into the database for further use.