Nowadays, credit classification models are widely applied because they can help financial decision-makers to handle credit classification issues. Among them, artificial neural networks (ANNs) have been widely accepted as the convincing methods in the credit industry. In this paper, we propose a pruning neural network (PNN) and apply it to solve credit classification problem by adopting the well...

this paper presents the application of radial basis neural networks to the development of a novel method for the condition monitoring and fault diagnosis of synchronous generators. in the proposed scheme, flux linkage analysis is used to reach a decision. probabilistic neural network (pnn) and discrete wavelet transform (dwt) are used in design of fault diagnosis system. pnn as main part of thi...

In this study, it was aimed to develop an accurate forecasting model for the monthly electricity demand of Turkey in medium-term. For purpose, Group Method Data Handling (GMDH)-type Neural Network (NN) approach used structure a nonlinear time-series based model. A large dataset containing considered period 2003-2018. The developed tested 2019/01-2019/11 order determine generalization ability te...

Among the foremost frequent and vital tasks for hydrologist is to deliver a high accuracy estimation on hydrological variable, which reliable. It essential flood risk evaluation project, hydropower development developing efficient water resource management. Presently, approach of Group Method Data Handling (GMDH) has been widely applied in modelling sector. Yet, comparatively, same tool not vas...

Shear wave velocity (VS) is one of the most important parameters in deep and surface studies estimation geotechnical design parameters. This parameter widely utilized to determine permeability porosity, lithology, rock mechanical parameters, fracture assessment. However, measuring this either impossible or difficult due challenges related horizontal deviation wells difficulty reaching cores. Ar...

This study concerns numerical simulation, modeling and optimization of aerodynamic stall control using a synthetic jet actuator. The numerical simulation was carried out by a large-eddy simulation that employs a RNG-based model as the subgrid-scale model. The flow around a NACA0015 airfoil, including a synthetic jet located at 10 % of the chord, is studied under Reynolds number Re = 12.7 × 10 a...

In this study, silk fibroin was extracted from cocoons of silkworms and fabricated into nonwoven mats by electrospinning method. A new model based on the group method of data handling (GMDH) and artificial neural network (ANN) was developed for estimation of the average diameter of electrospun silk fibroin nanofibers. In this regard, concentration, flow rate, voltage, distance, and speed of col...

0957-4174/$ see front matter 2013 Elsevier Ltd. A http://dx.doi.org/10.1016/j.eswa.2013.01.060 ⇑ Tel.: +385 1 4561191. E-mail address: [email protected] The main disadvantage of self-organizing polynomial neural networks (SOPNN) automatically structured and trained by the group method of data handling (GMDH) algorithm is a partial optimization of model weights as the GMDH algorithm optimizes on...

This paper proposes a new passive robust fault detection scheme using non-linear models that include parameter uncertainty. The nonlinear model considered here is described by a group method of data handling (GMDH) neural network. The problem of passive robust fault detection using models including parameter uncertainty has been mainly addressed by checking if the measured behaviour is inside t...