This paper presents the results of the General Regression Neural Networks applications for the prediction of propagation path loss in a specific urban environment. We have studied two neural network models; the first one is used for path loss prediction while the second one is a prediction model using error control. The performances of the neural models are compared to the path loss values meas...

In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...

In this research, a hybrid wavelet-artificial neural network (WANN) and a geostatistical method were proposed for spatiotemporal prediction of the groundwater level (GWL) for one month ahead. For this purpose, monthly observed time series of GWL were collected from September 2005 to April 2014 in 10 piezometers around Mashhad City in the Northeast of Iran. In temporal forecasting, an artificial...

In this paper, a genetic algorithm (GA) has been used to predict the vapor pressure of pure organic compounds based on Riedel equation. Initially, the coefficients of Riedel equation were optimized. Then, a new term was added to the original Riedel equation to reduce error of the model in prediction of vapor pressures of pure materials. 110 components at two different pressures (10 and 100 kPa)...

Aims: To study the refractive outcome of cataract surgery employing IOLMaster biometry data and to compare it with that of applanation ultrasonography in a prospective study of 100 eyes that underwent phacoemulsification with intraocular lens implantation. Methods: The Holladay formula using IOLMaster data was employed for the prediction of implanted intraocular lenses (IOLs). One month after c...

The dorsal anterior cingulate cortex (dACC) has been implicated in a variety of cognitive control functions, among them the monitoring of conflict, error, and volatility, error anticipation, reward learning, and reward prediction errors. In this work, we used a Bayesian ideal observer model, which predicts trial-by-trial probabilistic expectation of stop trials and response errors in the stop-s...

AIMS To study the refractive outcome of cataract surgery employing IOLMaster biometry data and to compare it with that of applanation ultrasonography in a prospective study of 100 eyes that underwent phacoemulsification with intraocular lens implantation. METHODS The Holladay formula using IOLMaster data was employed for the prediction of implanted intraocular lenses (IOLs). One month after c...

PURPOSE To evaluate the accuracy of intraocular lens power estimation in eyes having phacovitrectomy for rhegmatogenous retinal detachment. METHODS Retrospective case review of 100 consecutive eyes that underwent phacovitrectomy for rhegmatogenous retinal detachment. Axial lengths were measured using optical biometry and/or ultrasound A-scan. Achieved and predicted refraction were compared to...

The CERCHAR abrasivity test is very popular for determination of rock abrasivity. An accurate estimation of the CERCHAR abrasivity index (CAI) is useful for excavation operation costs. This paper presents a model to calculate CAI based on the gene expression programming (GEP) approach. This model is trained and tested based on a database collected from the experimental results available in the ...