Nowadays, modern engineering systems require sophisticated maintenance strategies to
ensure their correct performance. Maintenance has become one of the most important tasks …

Reinforcement learning is one of the sub of machine learning. A machine learning agent
learns from the feedback of the try-and-error in order to predict their next step. Machine …

Reinforcement learning (RL) has been applied to many fields and applications, but there are
still some dilemmas between exploration and exploitation strategy for action selection policy …

Waterflooding optimization in closed-loop management of the oil reservoirs is always
considered as a challenging issue due to the complicated and unpredicted dynamics of the …

Autonomous vehicles can reduce labor power during cargo transportation, and then improve
transportation efficiency, for example, the automated guided vehicle (AGV) in the warehouse …

This paper addresses a new method for combination of supervised learning and
reinforcement learning (RL). Applying supervised learning in robot navigation encounters …

In this paper, a dynamic fuzzy energy state based AODV (DFES-AODV) routing protocol for
Mobile Ad-hoc NETworks (MANETs) is presented. In DFES-AODV route discovery phase …

In order to get natural and intuitive physical interaction in the pose adjustment of the
minimally invasive surgery manipulator, a hybrid variable admittance model based on Fuzzy …

Parameter inversions in oil/gas reservoirs based on well test interpretations are of great
significance in oil/gas industry. Automatic well test interpretations based on artificial …

Operational instructions have a major role in improving water delivery performance in
irrigation canals. Of different delivery systems, on‐request systems have higher flexibility …