One of the most important issues always facing banks and financial institutes is the issue of credit risk or the possibility of failure in the fulfillment of obligations by applicants who are receiving credit facilities. The considerable number of banks’ delayed loan payments all around the world shows the importance of this issue and the necessary consideration of this topic. Accordingly...

estimation of pure runoff is a house virtually is complex and different methods of calculation have been proposed. modern methods of solving problems in river engineering and water homes and assess the flow method is used, is that the artificial network pattern of human brain neural network training process, while implementation of the internal relationships between the data and discover for ot...

this paper presents a new model for predicting the compressive strength of steel-confined concrete on circular concrete filled steel tube (ccfst) stub columns under axial loading condition based on artificial neural networks (anns) by using a large wide of experimental investigations. the input parameters were selected based on past studies such as outer diameter of column, compressive strength...

Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications that includes, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. Neural Network (NN) with its inherent learning ability offers promising solutions for handwritten characte...

Compressive strength and concrete slump are the most important required parameters for design, depending on many factors such as concrete mix design, concrete material, experimental cases, tester skills, experimental errors etc. Since many of these factors are unknown, and no specific and relatively accurate formulation can be found for strength and slump, therefore, the concrete properties ca...

objective(s): this study aims to evaluate and predict the thermal conductivity of iron oxide nanofluid at different temperatures and volume fractions by artificial neural network (ann) and correlation using experimental data. methods: two-layer perceptron feedforward artificial neural network and backpropagation levenberg-marquardt (bp-lm) training algorithm are used to predict the thermal cond...

In machine learning and statistics, feature selection is the technique of selecting a subset of relevant features for building robust learning models. In this paper we propose a bio-inspired BAT algorithm as feature selection method to find the optimal features from the KDDCup’99 intrusion detection dataset obtained from UCI Machine Learning repository. Neural Networks (NN) as a classifier coll...

This paper investigates the generation of neural networks through the induction of binary trees of threshold logic units (TLUs). Initially, we describe the framework for our tree construction algorithm and show how it helps to bridge the gap between pure connectionist (neural network) and symbolic (decision tree) paradigms. We also show how the trees of threshold units that we induce can be tra...

Deep neural networks have proved to be a very effective way to perform classification tasks. They excel when the input data is high dimensional, the relationship between the input and the output is complicated, and the number of labeled training examples is large [Szegedy et al., 2015, Wu et al., 2016, Jozefowicz et al., 2016, Graves et al., 2013]. But it is hard to explain why a learned networ...