a Quantile Deep Reinforcement Learning (Q-DRL) algorithm. The research will provide a new level of understanding the …

a Quantile Deep Reinforcement Learning (Q-DRL) algorithm. The research will provide a new level of understanding the …

, shifting from data-driven, discriminative AI tasks toward sophisticated, creative tasks through generative AI. Leveraging deep …

, mimicking the human brain. In this study, we use ANNs for designing deep underground supports. We develop a predictive model for … the ultimate axial capacity of deep foundations called drilled shafts, commonly used as support for highways, bridges and … drilled shafts. The data used in this study are load tests collected from the extended version of the Nevada Deep Foundation …

An Autoencoder (AE) is an independent feature extractor from data samples and a deep network can be obtained by … stacking several AEs. This paper presents a novel hybrid stacked Autoencoder-based Deep Kernel-based Random Vector Functional … dispenses the random choices of weights and biases, unlike the stacked Deep Random Vector Functional Link Network-AE (DRVFLN …