 Conventional financial conditions and empirical evidence related to the implied volatility are incorporated into the neural network architecture design and model training including no static arbitrage,  boundaries, asymptotic slope and volatility smile.
<clarity>  Conventional financial conditions and empirical evidence related to the implied volatility are incorporated into the neural network architecture design and model training including no static arbitrage,  boundaries, asymptotic slope and volatility smile.
 It can incorporate the related properties from existing mathematical models and empirical findings, including no static arbitrage, boundaries, asymptotic slope and volatility smile.