CO2–brine–rock interaction impacts the behavior and efficiency of CO2 geological storage;
a thorough understanding of these impacts is important. A lot of research in the past has …

The paper considers missing data management task in smart systems. The main strategies
of missing data management in handling missing data are analyzed. A prediction method for …

To meet the ever-increasing global energy demands, it is more necessary than ever to
ensure increments in the recovery factors (RF) associated with oil reservoirs. Owing to this …

The oil and gas industry faces several challenges associated with managing massive
datasets and extracting relevant information. The machine learning tools have proven to be …

In the new millennium, with chaotic situation that exist in the world, people are threaten with
multifarious terrorist attacks. There have been several intelligent ways in order to recognize …

In this research, we propose a novel fractional gradient descent-based learning algorithm
(FGD) for the radial basis function neural networks (RBF-NN). The proposed FGD is the …

The current research was an effort to simulate landfill leachate penetration into groundwater
using fuzzy logic and neural network modeling approaches. The obtained models were …

In this paper, we propose a novel adaptive kernel for the radial basis function neural
networks. The proposed kernel adaptively fuses the Euclidean and cosine distance …

Deep eutectic solvents (DES) are used as a green sustainable alternative to room
temperature ionic liquids (RTILs), given their low cost and environmentally friendly nature. In …

One billion people worldwide experience intermittent water supply (IWS), in which piped
water is delivered for limited durations. Households with IWS must invest in water storage …