in this paper, the artificial neural network (ann) approach is applied for forecasting groundwater level fluctuation in aghili plain,southwest iran. an optimal design is completed for the two hidden layers with four different algorithms: gradient descent withmomentum (gdm), levenberg marquardt (lm), resilient back propagation (rp), and scaled conjugate gradient (scg). rain,evaporation, relative...

Basic definitions concerning the multi-layer feed-forward neural networks are given. The back-propagation training algorithm is explained. Partial derivatives of the objective function with respect to the weight and threshold coefficients are derived. These derivatives are valuable for an adaptation process of the considered neural network. Training and generalisation of multi-layer feed-forwar...

At present, polyhydroxyalkanoates (PHAs) have been considered as a promising alternative to conventional plastics due to their diverse variability in structure and rapid biodegradation. To ensure cost competitiveness in the market, thermoseparating aqueous two-phase extraction (ATPE) with the advantages of being mild and environmental-friendly was suggested as the primary isolation and purifica...

In this paper, we have designed and developed a technique for burning area identification using Intensity Hue Saturation (IHS) transformation and image segmentation. The process of identifying the burnt area in proposed technique consists of four steps such as: IHS transformation, object segmentation, identification of smoke area using Feed-Forward Neural Network (FFNN) and discovering burning ...

Evapotranspiration (ET) is a significant aspect of the hydrologic cycle, notably in irrigated agriculture. Direct approaches for estimating reference evapotranspiration (ET0) are either difficult or need large number inputs that not always available from meteorological stations. Over 6-year period (2006–2011), this study compares Feed Forward Neural Network (FFNN), Radial Basis Function (RBFNN)...

life style and life expectancy of inhabitants have been affected by the increase of particulate matter 10 micrometers or less in diameter (pm10) in cities and this is why maximum pm10 concentrations have received extensive attention. an early notice system for pm10 concentrations necessitates an accurate forecasting of the pollutant. in the current study an artificial neural network was used t...

mobile robot navigation is one of the basic problems in robotics. in this paper, a new approachis proposed for autonomous mobile robot navigation in an unknown environment. the proposedapproach is based on learning virtual parallel paths that propel the mobile robot toward the trackusing a multi-layer, feed-forward neural network. for training, a human operator navigates themobile robot in some...

In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward ne...

Because of increasingly common damage and thefts of the transmission towers, a new function is proposed to enhance the state maintenance of transmission lines. It relies on the monitoring of the high-voltage transmission towers to ensure the reliability and safety of the power grid operation. An approach which combines Independent Component Analysis (ICA) with neural network based on Particle S...

Vibration based techniques of structural damage detection using model updating method, are computationally expensive for large-scale structures. In this study, after locating precisely the eventual damage of a structure using modal strain energy based index (MSEBI), To efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, the M...