**4. Simulation Model**

In this paper, an artificial neural network (ANN)-based model has been developed in the MATLAB environment. The aim was to predict (i) the supply air temperature, (ii) the supply air relative humidity, (iii) the opening percentage of the valve supplying the post-heating coil, (iv) the opening percentage of cooling coil valve, and (v) the opening percentage of the steam humidifier valve. This ANN has been first validated with measured data and then coupled with a dynamic simulation model developed in TRNSYS environment in order to simulate (i) the return air temperature; (ii) the return air relative humidity; as well as (iii) the electric energy consumptions (not measured) of the heat pump, the refrigerating system, the steam humidifier, the supply air fan, and the return air fan with the aim of rating the effects of the selected faults on both energy consumption as well occupant indoor thermo-hygrometric comfort. The artificial neural network-based model is described in Sections 4.1 and 4.1.1–4.1.3, while the description of the TRNSYS model is reported in Section 4.2.
