پیش بینی و بهینه سازی صدا های موجود در هوا و سازه های کف-سقف با استفاده از هوش محاسباتی

First a simple neural network (NN) model for predicting the airborne sound transmission of typical floor–ceiling constructions is presented and explained in detail. This model is accessible to researchers with knowledge of neural network analysis (NNA) for further sophistication, specialisation or hybridisation. The model may also be used by architects and others with no knowledge of NNA and no access to any specialised neural network software. Evolutionary algorithms (EAs) were then applied to search the multidimensional space created by the neural network model in order to optimise the airborne sound transmission of floor–ceiling constructions within the range of design parameters utilised in buildings.