Artificial Neural Networks to Optimize Zero Energy Building (ZEB) Projects from the Early Design Stages

Building energy modeling (BEM) is used to support (nearly) zero-energy building (ZEB) projects, since this kind of software represents the only available option forecast consumption with high accuracy. BEM may also be during preliminary analyses or feasibility studies, but simulation results are usually too detailed for stage project. Aside from that, when optimization algorithms used, implied number simulations causes very long calculation times. Therefore, designers could discouraged extensive use conduct analyses. Thus, they prefer study and compare a limited amount acknowledged alternative designs. In relation problem, scope present obtain an easy-to-use tool quickly no direct fast comparative at early stages projects. response, set automatic assessment tools was developed based on machine learning techniques. The forecasting artificial neural networks (ANNs) that able estimate automatically any building, descriptive data property. ANNs Po Valley area in Italy as pilot case study. useful assess demand even considerable buildings by comparing different design options, help