estimating of forest equipment productivity is an important aspect of managing cost in forestry, which leads to reduction of operations expenses. in other words, high capital cost in forest harvesting, is a good reason to argue forest engineering research and time modeling. this paper applied one of the artificial intelligence subsets, which are called artificial neural networks (anns), to pred...

The forecast of fluctuations and prices is the major concern in financial markets. Thus, developing an accurate and robust forecasting decision model is critically favorable to the investors. As gold has shown a special capability to smooth inflation fluctuations, governors use gold as a price controlling lever. Thus, more information about future gold price trends will help to make the firm de...

The paper describes an artificial neural network (ANN) model to predict the height of destressed zone (HDZ) which is taken as equivalent to the combined height of caved and fractured zones above the mined panel in longwall mining. For this, the suitable datasets have been collected from the literatures and prepared for modeling. The data were used to construct a multilayer perceptron (MLP) netw...

This paper compares, for a microfinance institution, the performance of two individual classification models: Logistic Regression (Logit) and Multi-Layer Perceptron Neural Network (MLP), to evaluate the credit risk problem and discriminate good creditors from bad ones. Credit scoring systems are currently in common use by numerous financial institutions worldwide. However, credit scoring using ...

The divergent auto-encoder (Kurtz, 2007) offers an alternative to the multi-layer perceptron (MLP) for classification learning via back-propagation. The artificial neural network classifies based on its success reconstructing the input features (from shared, reduced dimensionality recodings) in terms of a generative model of each category. Successful simulations of rapid human learning of eleme...

Abstract— An educational platform is presented here for the beginner students in the Simulation and Artificial Intelligence sciences. It provides with a start point of building and simulation of the manipulators, especially of 2R planar Robot. It also displays a method to replace the inverse kinematic model (IKM) of the Robot with a simpler one, by using a Multi-Layer Perceptron Neural Network ...

Abstract Groundwater is often one of the significant natural sources freshwater supply, especially in arid and semi-arid regions, paramount importance. This study provides a new high accurate technique for forecasting groundwater level (GWL). The artificial intelligence (AI) models include neural network (ANN) multi-layer perceptron (MLP) radial basis function (RBF), adaptive neural-fuzzy infer...

Artificial neural networks (ANNs) have become one of the most promising tools for rainfall simulation since a few years ago. However, most of the researchers have focused on rainfall intensity records as well as on watersheds, which generally are utilized as input records of other hydro-meteorological variables. The present study was conducted in Kechik station, Golestan Province (northern Iran...

We have investigated the use of an Artificial Neural Network (ANN) for the assessment of fall-risk (FR) in patients with different neural pathologies. The assessment integrates a clinical tool based on a wearable device (WD) with accelerometers (ACCs) and rate gyroscopes (GYROs) properly suited to identify trunk kinematic parameters that can be measured during a posturography test with differen...