The growing interest in Artificial Intelligence is pervading several domains of technology and
robotics research. Only recently has the space community started to investigate deep …

Artificial neural network (ANN) model involves computations and mathematics, which
simulate the human–brain processes. Many of the recently achieved advancements are …

Rate of Penetration (ROP) can be considered as a crucial factor in optimization and cost
minimization of drilling operations. In order to predict ROP with satisfactory precision, some …

Uniform seed spacing within the row is the most desirable prerequisite for better crop yield.
The seeding uniformity of a pneumatic seed metering device is significantly affected by its …

Predicting the drilling rate of penetration (ROP) is one approach to optimizing drilling
performance. However, as ROP behavior is unique to specific geological conditions its …

The Kalman filter variants extended Kalman filter (EKF) and error-state Kalman filter (ESKF)
are widely used in underwater multi-sensor fusion applications for localization and …

Training artificial neural networks is considered as one of the most challenging machine
learning problems. This is mainly due to the presence of a large number of solutions and …

This paper presents a novel technique, combining neural network and Kalman filter, for state
estimation. The proposed solution provides the estimates of the system states while also …

One of the most prevalent problems in drilling industry is lost circulation which causes
intense increase in drilling expenditure as well as operational obstacles such as well …

Deep neural networks (DNN) can model nonlinear relations between physical quantities.
Those DNNs are embedded in physical systems described by partial differential equations …