Evaluation and Study of Growth of Energy-Saving Building Based on Cascade Neural Network

The energy-saving gap of building is serious. In practical matters of building engineering, the input process of time-varying system can be divided into several stages. In every stage, the system has its own rules and features. At present, various evaluation methods are slow in solving this matter. Cascade neural network can properly describe the growth continuity of each part of building energy-saving. In this paper, we applied cascade neural network to the growth evaluation of building energy-saving to effectively monitor whether building energy-saving is out of joint.