in this paper, the artificial neural network (ann) approach is applied for forecasting groundwater level fluctuation in aghili plain,southwest iran. an optimal design is completed for the two hidden layers with four different algorithms: gradient descent withmomentum (gdm), levenberg marquardt (lm), resilient back propagation (rp), and scaled conjugate gradient (scg). rain,evaporation, relative...

One of the most influential factors in the quality of the solutions found by an evolutionary algorithm is the appropriateness of the fitness function. Specifically in data mining, in where the extraction of useful information is a main task, when databases have a great amount of examples, fitness functions are very time consuming. In this sense, an approximation to fitness values can be benefic...

This paper investigates neural network based estimation of NOx emissions in a thermal power plant, fed with both oil and methane fuels. Two types of neural network namely a novel ‘eng-genes’ architecture and a Multilayer Perceptron (MLP) have been developed, both being optimised using genetic algorithms. Due to the local nature of the NOx generation process, operational information on the burne...

Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data...

Online social networks like Instagram are places for communication. Also, these media produce rich metadata which are useful for further analysis in many fields including health and cognitive science. Many researchers are using these metadata like hashtags, images, etc. to detect patterns of user activities. However, there are several serious ambiguities like how much reliable are these informa...

In this paper, the estimations of mechanical property of rolled steel bar by using quantum neural network (QNN) were proposed. Based on the learning capability of neural network, the nonlinear, complex relationships among the steel bar, the billet materials and the control parameters of production could be automatically developed. Such an artificial intelligent (AI) estimator then can help the ...

⇑ Corresponding author. Tel.: +886 928722593; fax E-mail addresses: [email protected] (Y.-J. Chen (H.-C. Huang), [email protected] (R.-C. Hwang). This paper presents the estimations of ammonia concentration by using neural network (NN) models. The shear horizontal surface acoustic wave (SH-SAW) devices coated with L-glutamic acid hydrochloride and polyaniline (PANI) film, respectively, were ap...