Neural Networks (ANN)
Role of Artificial Neural Networks (ANN) in Image Processing
... Artificial Neural Networks (ANNs) as a means of image processing. ANN is a powerful technology used to solve many real-world problems in the world of image ...of Neural-network based ...
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A Hybrid Method for Compression of Solar Radiation Data Using Neural Networks
... Artificial Neural Networks (ANN), namely Multi-layer perceptron neural network (MLPNN), Cascade feed forward back propagation (CFNN) and Elman back propagation ...three ANN models ...
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Sinusoidal Neural Networks: Towards ANN that Learns Faster
... Sinusoidal Neural Networks ...artificial neural network (ANN) algorithm that can learn ...new neural network algorithm called SNN is ...proposed neural network can reach high ...
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Modelling of Multi Layer Feed forward Neural Networks to Determine the Compressive Strength of Marmara Region Aggregate's Concrete
... Artificial neural networks are inspired by biological central nervous systems of brain and are used to estimate or approximate functions that can depend on a large number of inputs and are generally ...
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Neural Networks in power system operation and control
... Artificial Neural Networks (ANN) technique plays an important ...a neural network technique can be used to design an MPPT controller for photovoltaic generators, enabling to improve their ...
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Forecasting the yield and direction of the Australian 10 year Commonwealth Treasury Bond using artificial neural networks
... This paper is concerned with the application of artificial neural networks (ANN) to the forecasting of the time series generated by the 10 Year Commonwealth Treasury Bond [r] ...
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An approach of curing Depression by Artificial Neural Networks (ANN)
... recoverable. It has also been observed that neurological effects caused due to depression persist throughout the life. In this age of advent of computational techniques, cure for depression can be done utilizing the ...
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The use of artificial neural networks for identifying sustainable biodiesel feedstocks
... of ANN modeling techniques in predicting performance parameters of internal combustion engines has gained in popularity over the last few ...using ANN. Cay et al. [166] developed an ANN model to ...
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Evaluation of Three Evaporation Estimation Techniques In A Semi-Arid Region (Omar El Mukhtar Reservoir Sluge, Libya- As a case Study)
... (artificial neural networks (ANN), Multiple linear regression (MLR) and response surface methods (RSM) ) were developed, to assess the estimation of monthly evaporation records from 2001 to 2009; ...
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Non linear algorithm analysis of large scale traffic data for systematic pattern detection
... artificial neural networks have been widely used for estimating traffic parameters and it can be conclude that Artificial Neural Network (ANN) technique may be used to estimating missing data ...
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Forecasting of Pakistans Import Prices of Black Tea Using ANN and SARIMA Model
... Artificial Neural Networks (ANN) models are used to forecast the Pakistan’s import prices of black tea by using data for the time period Jan 2004 to Dec ...and ANN models are evaluated on the ...
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1. Diagnosing alzheimer’s disease and mild cognitive impairment with modalities: a survey
... Artificial Neural Networks(ANN), Recurrent Neural Networks(RNN), Recursive feature elimination, hybrid based features, Spherical harmonics -Point distribution model(SPHARM-PDM), ...
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Prediction of the kind of sprouts of Cruciferae family based on artificial neural network analysis
... tificial neural networks (ANN) are a convenient tool for predicting the kind of sprouts originated from Cruciferae family based on the contents of bioactive ...artificial neural ...
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Study on Experiments of Artificial Neural Network Using Spatial Data
... Artificial Neural Network is one of the artificial intelligence models that are designed similar to biological neurons in humans who have the ability to tolerate mistakes and do whatever training patterns are ...
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Artificial Neural Network Models Investigation for Euphrates River Forecasting & Back Casting
... best ANN artificial neural networks model for simulation and forecasting of Euphrates river flow downstream Al-Hindiyaha barrage was investigated by applying different architectures of ANN ...
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Classification Techniques for Predicting Graduate Employability
... Artificial Neural Networks (ANN), Decision Tree and Support Vector Machine (SVM), factors that affect graduates employability such as academic’s achievement, differences in academic’s discipline, ...
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Quantitative structure activity relationship studies of anti-proliferative activity of some indole derivatives combining DFT calculations and statistical results
... artificial neural networks (ANN) can be used to generate predictive models of quantitative structure-activity relationships (QSAR) between a set of molecular descriptors obtained from the MLR, and ...
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Optimization of surface roughness using RSM and ANN modelling on thin walled machining under biodegradable cutting fluids
... The purpose of this paper is to compare the utilized of Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) in prediction and optimization surface roughness milling thin-wall ...
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A FORMAL DEFINITION OF METRICS FOR OBJECT ORIENTED DESIGN: MOOD METRICS
... artificial neural networks (ANN) research has received a great deal of attention from the science and technology circles over the world ...given ANN, it has also been reported fairly good ...
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Article Description
... artificial neural networks is that there are different architectures, which consequently require different types of algorithms, but despite being an apparently complex system, a neural network is ...
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