In today's interconnected society, cyberattacks have become more frequent and
sophisticated, and existing intrusion detection systems may not be adequate in the complex …

Abstract Industrial Cyber-physical systems (ICPSs), integrating communication, computation
and control of industrial processes are referred to as a core technology to approach the …

Although many deep learning models-based medical applications are performance-driven,
ie, accuracy-oriented, their explainability is more critical. This is especially the case with …

Fault detection and diagnosis in the chemical industry is a challenging task due to the large
number of measured variables and complex interactions among them. To solve this …

Short-term load forecasting is the basis of power system operation and analysis. In recent
years, the use of a deep belief network (DBN) for short-term load forecasting has become …

Deep belief network (DBN) is an import deep learning model and restricted Boltzmann
machine (RBM) is one of its basic models. The traditional DBN and RBM have numerous …

深度信念网络(Deep belief network, DBN) 是一种基于深度学习的生成模型,
克服了传统梯度类学习算法在处理深层结构所面临的梯度消失问题, 近几年来已成为深度学习 …

This new volume discusses state-of-the-art deep learning techniques and approaches that
can be applied in biomedical systems and health informatics. Deep learning in the …

Nowadays the use of deep network architectures has become widespread in machine
learning. Deep belief networks (DBNs) have deep network architectures to create a powerful …

In recent days, systems are designed to have better classification based on input. The inputs
vary based on the application that is intended, viz., retina image for detection of diabetic …