Production of highly viscous tar sand bitumen using Steam Assisted Gravity Drainage (SAGD) with a pair of horizontal wells has advantages over conventional steam flooding. This paper explores the use of Artificial Neural Networks (ANNs) as an alternative to the traditional SAGD simulation approach. Feed forward, multi-layered neural network meta-models are trained through the Back-...

Back-propagation modeling of viscosity and shear stress Ionic-MXene nanofluid is carried out in this work. The data for 0.05, 0.1, 0.2 mass concentration (mass%) are collected from the experimental analysis. Shear as a function rate mass% MXene nanoparticles used input. Additionally, temperature % separately. Based on possible combinations, five back-propagation algorithms developed. In each al...

In this study, artificial neural network was used to predict the microhardness of Al2024-multiwall carbon nanotube(MWCNT) composite prepared by mechanical alloying. Accordingly, the operational condition, i.e., the amount of reinforcement, ball to powder weight ratio, compaction pressure, milling time, time and temperature of sintering as well as vial speed were selected as independent input an...

The color of the blends of pre-colored fibers depends on the ratio of each fiber in the blends. Some theories have been introduced for color matching of blends of pre-colored fibers. Most however, are restricted in scope and accuracy. Kubelka and Munk presented the most applicable theory, which is still used in industry. In this work, the classical Kubelka-Munk method for color prediction of a ...

To counter the drawbacks that Waibel 's time-delay neural networks (TDW) take up long training time in phoneme recognition, the paper puts forward several improved fast learning methods of 1PW. Merging unsupervised Oja's rule and the similar error back propagation algorithm for initial training of 1PhW weights can effectively increase convergence speed, at the same time error firnction almost m...

Artificial Neural Networks are information processing systems. Over the past several years, these algorithms have received much attention for their applications in pattern completing, pattern matching and classification and also for their use as a tool in various areas of problem solving. In this work, an Artificial Neural Network model is presented for predicting the tensile properties of co...

Scour in the downstream of hydraulic structures is a phenomenon which usually occurs due to exceeding the velocity or shear stress from a critical level. In this paper by using the laboratory data by Borman- Jouline and De-Agostino research, it was tried to get more accurate equations in order to calculate the maximum depth of scour in the downstream of the water level regulation structures. Co...

In this study, activated sludge process for wastewater treatment in a refinery was investigated. For such purpose, a laboratory scale rig was built. The effect of several parameters such as temperature, residence time, effect of Leca (filling-in percentage of the reactor by Leca) and UV radiation on COD removal efficiency were experimentally examined. Maximum COD removal efficiency was obtained...

An anti-Hebbian local learning algorithm for two-layer optical neural networks is introduced. With this learning rule, the weight update for a certain connection depends only on the input and output of that connection and a global, scalar error signal. Therefore the backpropagation of error signals through the network, as required by the commonly used back error propagation algorithm, is avoide...