Heat transfer fluids have inherently low thermal conductivity that greatly limits the heat exchange efficiency. While the effectiveness of extending surfaces and redesigning heat exchange equipments to increase the heat transfer rate has reached a limit, many research activities have been carried out attempting to improve the thermal transport properties of the fluids by adding more thermally c...

Asphaltene precipitation is traditionally modeled using polymer solution theories or cubic equations of state. We propose another approach based on artificial neural network technique to model onset of precipitation of dissolved asphaltene in the solution of solvent + precipitant. A mathematical model based on feed-forward artificial neural network technique, which takes advantage of a modified...

This paper presents a strategy for controlling inverter-interfaced DERs within a microgrid using an artificial neural network. The neural network implements a dynamic programming algorithm and is trained with a new Levenberg-Marquardt backpropagation algorithm. Hardware experiments were conducted to evaluate the performance of the neural network vector control method. They showed that the neura...

In order to effectively implement a good model based control strategy, the combination of different linear models working at various operating regions are mostly utilised since a single model that can operate in that fashion is always a difficult task to develop. This work presents the use of soft computing approaches such as evolutional algorithm called simulated annealing (SA), a genetic algo...

Performance of four types of functionally different artificial neural network (ANN) models, namely Feed forward neural network, Elman type recurrent neural network, Input delay neural network and Radial basis function network and fourteen types of algorithms, namely Batch gradient descent (traingd), Batch gradient descent with momentum (traingdm), Adaptive learning rate (traingda), Adaptive lea...

the method of artificial neural network is used as a suitable tool for intelligent interpretation of gravity data in this paper. we have designed a hopfield neural network to estimate the gravity source depth. the designed network was tested by both synthetic and real data. as real data, this artificial neural network was used to estimate the depth of a qanat (an underground channel) located at...

The viscosities of aqueous two phase system containing bovine serum albumin (BSA) were predicted by artificial neural network (ANN) as a function of concentration of poly-ethylene-glycol (PEG), concentration of BSA and temperature. A three layer feed forward neural network based on Levenberg-Marquardt (LM) algorithm which consisted of three input neurons, 10 hidden neurons and one output neuron...

In-situ bioremediation is one of the most economic techniques for groundwater remediation. BIOPLUME III is used to simulate the transport and biodegradation of contaminant. During optimal design of bioremediation system, the simulated BIOPLUME III data for the entire aquifer is usually called several times by optimization algorithm to optimize the system. This is a very time consuming process a...