Large and Tall Buildings

Abstract

Large and Tall buildings can be broadly classified into three groups: sprawling, squat, or tall. The decision to build a particular type of large building can be based on a vast number of attributes. A building construction expert’s analysis of seventy international building projects was used as input to further decision support and data mining analyses. Decision models were developed that incorporated customer values of proposed construction project attributes. Data mining was used to model the feasibility of construction projects from their input attributes. On this basis, we propose a novel way of integrating data mining and decision support methods, where both techniques are used. In this approach both techniques are employed to utilize the same input vectors. While decision support models are designed to assess and possibly maximize utility, data mining models provide a test for feasibility.