modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. thisstudy made us of adaptive neuro-fuzzy ...

Statistical mechanical and artificial intelligence models are developed to predict the volumetric properties of lubricants under different conditions. It is shown that the knowledge of just liquid density at room temperature is satisfactory to approximate the PVT properties of pure lubricants in various conditions. As well, the performance of an artificial neural network (ANN) based on back pro...

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-...

We observe the propagation of information in a system of self-replicating strings of code (“Artificial Life”) as a function of fitness and mutation rate. Comparison with theoretical predictions based on the reaction-diffusion equation shows that the response of the artificial system to fluctuations (e.g. velocity of the information wave as a function of relative fitness) closely follows that of...

The wire medium is a type of complex artificial material we conceptually envision as many identical finitelength, parallel, thin wire inclusions embedded within a host medium. It is representative of a class of novel artificial materials characterized by long thin inclusions. Unlike some conventional artificial material, the inclusions of this class are not necessarily electrically short. Here,...

We observe the propagation of information in a system of self-replicating strings of code (“Artificial Life”) as a function of fitness and mutation rate. Comparison with theoretical predictions based on the reaction-diffusion equation shows that the response of the artificial system to fluctuations (e.g. velocity of the information wave as a function of relative fitness) closely follows that of...

The paper presents a method for classifying coffees according to their scents using artificial neural network (ANN). The proposed method of uses genetic algorithm (GA) to determine the optimal parameters and topology of ANN. It uses adaptive back-propagation to accelerate the training process so that the entire optimization process can be achieved in an accelerated time. The optimized ANN has s...

in this work, response surface methodology (rsm) and artificial neural network (ann) were used to predict the decolorization efficiency of reactive red 33 (rr 33) by o3/uv process in a bubble column reactor. the effects of four independent variables including time (20-60 min), superficial gas velocity (0.06-0.18 cm/s), initial concentration of dye (50-150 ppm) and ph (3-11) were investigated us...

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...