… This chapter evaluates various machine learning and deep learning algorithms and their
use relative to analytics solutions that rapidly grow in enterprise and on industrial data arena. It …

… We present how different machine learning algorithms can be applied in individual layer
and cross-layer design to guarantee the QoS requirements of massive IIoT. 4. To demonstrate …

… such as deep learning (DL). Notably, DL algorithms, when applied to the Industrial IoT (IIoT),
can … deep learning in industrial Internet of Things,” IEEE Internet Things J., vol. 7, no. 5, pp. …

… internet of things (IoT) applications has been extended to the industrial sector, emerging
the industrial internet of things … and superior performance to industrial operations. The …

… IV-B3, the time complexity of our deep learning algorithm f(x) equals θ(n2). … learning-based
transmission scheduling mechanism for the cognitive Internet of Things,” IEEE Internet Things …

… , the resource management algorithm will face some challenges if Q-learning is directly adopted
… mechanism for the cognitive Internet of Things,” IEEE Internet Things J., vol. 5, no. 4, pp. …

… In future work, we plan to apply different deep learning algorithms within the proposed
scheme along with working in different datasets in the area of critical Industrial control systems. …

… is based on the trial-and-error learning model, from the interaction with the … Industrial
Internet of Things intrusion detection system based on a deep reinforcement learning algorithm…

… [46] used DBN which adopted the greedy layer-by-layer learning algorithm to learn each
stack of RBM at a time to identify intrusion activities. Similarly, Gao et al [47] suggested the use …

… , we propose a reinforcement learning (RL)-empowered feed… First, by integrating RL and
machine learning (ML) algorithms, … industrial internet of things,” IEEE Internet Things J., vol. 6, no…