This study aimed to evaluate the efficiency of energy consumption and economic analysis of different watermelon cultivation systems in Fars Province of Iran. Watermelon production systems were classified into five systems, namely, custom tillage (group 1), conservation tillage (group 2), traditional planting (group3), semi mechanized planting (group 4), and mechanized planting (group 5). Data w...

The wearable electrocardiogram (W-ECG) signal inherently contains motion artifacts due to various body movements of the wearer. The W-ECG signals with four body movement activit ies (BMAs) ‒ left arm up-down, right arm up-down, waist-twist and walking of five healthy subjects have been acquired using the wearable ECG recorder. The classification of these four BMAs has been performed using artif...

This paper presents an alternative approach using the differential logic associated to Artificial Neural Networks (ANNs) in order to distinguish between inrush currents and internal faults in the protection of power transformers. The Alternative Transients Program (ATP) has been chosen as the computational tool to simulate a power transformer under fault and energization situations. The Radius ...

The main aim of this paper is to establish a reliable model of a process behavior both for the steady-state and unsteady-state regimes. The use of this accurate model allows distinguishing a normal mode from an abnormal one. Therefore the neural black-box identification by means of a NARX (Nonlinear Auto-Regressive with eXogenous) model has been chosen. It shows the choice and the performance o...

this paper presents the application of multivariate time series model (ardl) to investigate factors affecting bread waste and to explore the relationships among shortrun, longrun and error correction coefficient and the independent variables over the period 1978-2006. results reveal that gross national product and urbanization have positive effects on bread waste in the long term, while the bre...

This paper deals with artificial neural network (ANN) architecture, the multilayer Feed-forward (MLFF) network with back propagation learning. The training of an artificial neural network involves two passes. In the forward pass, the input signals propagate from the network input to the output. In the reverse pass the calculated error signals propagate backwards through the network where they a...

We report the development of a predictive model based on artificial neural network (ANN) for the estimation of flank and nose wear of uncoated carbide inserts during orthogonal turning of NST (Nigerian steel) 37.2. Turning experiments were conducted at different cutting conditions on a M300 Harrison lathe using Sandvic Coromant uncoated carbide inserts with ISO designations SNMA 120406 using fu...

A new classifier algorithm based on Multilayer Perceptron Neural Network (MPNN), Apriori association rules, and Particle Swarm Optimization (PSO) models is proposed. It provides a comprehensive analytic method for establishing an Artificial Neural Network (ANN) with self-organizing architecture by finding an optimal number of hidden layers and their neurons, less number of effective features of...