This study presents a new procedure based on Artificial Neural Network (ANN) for identification of double cracks in Functionally Graded Beams (FGBs). A cantilever beam is modeled using Finite Element Method (FEM) for analyzing a double-cracked FGB and evaluation of its first four natural frequencies for different cracks depths and locations. The obtained FEM results are verified against availab...

One of the processes used in production fertilizers, which has become an important part agriculture, is drying process. Determination proper parameters both terms product quality and efficiency. Regression methods are to determine process frequently. In this study, addition regression method, machine learning techniques also examined such as artificial neural network, long short term memory met...

We present our experiments applying, off-the-shelf, two existing Named Entity Recognition (NER) taggers for the Biomedical Abbreviation Recognition and Resolution (BARR) task at IberEval 2017. The first system is a Perceptron tagger based on sparse, shallow features whereas the second is a bidirectional Long-Short Term Memory neural network with a sequential conditional random layer above it (L...

introduction agriculture still constitutes the backbone of the rural economy and is an engine of rural household income growth in developing countries. according to the evidence, agriculture sector has an important role also in rural economy in islamic republic of iran. thus, in order to promote rural economy, rural development programs and policies have been focused on agricultural investments...

In this paper we present an adaptive appoach to observe the joint velocity for rigid robot manipulators. This approach is based on the neural network and sliding mode technique. The adopted neural network is of the MLP (Multi Layer Perceptron) type with one hidden layer. The functions of the dynamic model of the robot manipulator are assumed unknown. The neural network parameters are adapted on...

A sufficient condition that a region be classifiable by a two-layer feedforward neural net (a two-layer perceptron) using threshold activation functions is that either it be a convex polytope or that intersected with the complement of a convex polytope in its interior, or that intersected with the complement of a convex polytope in its interior or ... recursively. These have been called convex ...

We discuss a number of methods for estimating the standard error of predicted values from a multi-layer perceptron. These methods include the delta method based on the Hessian, bootstrap estimators, and the \sandwich" estimator. The methods are described and compared in a number of examples. We nd that the bootstrap methods perform best, partly because they capture variability due to the choice...