Search Results - feed-forward ((propagation algorithm) OR (selection algorithm))
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Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh
Published 2019“…The best result achieved for Pb2+ removal using ANFIS algorithm is with RE 7.078%. For As3+ removal using different adsorbents, two algorithms were applied for the modelling, the feed-forward back-propagation maximum RE achieved is 5.97% while, the NARX algorithm achieved better accuracy with maximum RE of 5.79%. …”
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2
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…ANN based STLF models commonly use back-propagation algorithm, which generally exhibits a slow and improper convergence that affects the forecast accuracy. …”
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3
Early detection of dengue disease using extreme learning machine
Published 2018“…Therefore, this research proposed an improved algorithm known as ELM which is an extension of Feed Forward Neural Network that utilize the Moore Penrose Pseudoinver matrix that gain the optimal weights of neural network architecture. …”
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Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column
Published 2003“…The topology of the ANN model was founded on multilayer feed forward network architecture and the training scheme conducted using back propagation algorithm. …”
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Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network
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Working Paper -
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Wind power prediction using Artificial Neural Network: article
Published 2010“…In order to get an accurate wind power prediction, several network structures, training algorithms and transfer functions have been developed and tested with different sets of data. …”
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Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding
Published 2007“…One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. The performance of Multilayer Feed Forward Artificial Neural Network performance in image compression using different learning algorithms is examined in this paper. …”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…ANN can be categorized into three main types: single layer, recurrent network and multilayer feed-forward network. In multilayer feed-forward ANN, the actual performance is highly dependent on the selection of architecture and training parameters. …”
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Power system security assessment using artificial neural network: article / Mohd Fathi Zakaria
Published 2010“…This paper presented an application of Artificial Neural Network (ANN) in steady state stability classifications. A multi layer feed forward ANN with Back Propagation Network algorithm is proposed in determining the steady state stability classifications. …”
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10
Wind power prediction using Artificial Neural Network
Published 2010“…In order to get an accurate wind power prediction, several network structures, training algorithms and transfer functions have been developed and tested with different sets of data. …”
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Classification of Agarwood using ANN
Published 2012“…The network developed based on three layers feed forward network and the back propagation learning algorithm was used in executing the network training. …”
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Early tube leak detection system for steam boiler at KEV power plant
Published 2023“…Backpropagation; Coal; Coal fired boilers; Engineering research; Engines; Fault detection; Fossil fuel power plants; Leak detection; Neural networks; Plant shutdowns; Steam power plants; Artificial neural network models; Coal-fired power plant; Feed-forward back propagation networks; Hidden layers; Neural network (nn); Training algorithms; Training function; Working properties; Boilers…”
Conference Paper -
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Training method for a feed forward neural network based on meta-heuristics
Published 2018“…This paper proposes a Gaussian-Cauchy Particle Swarm Optimization (PSO) algorithm to provide the optimized parameters for a Feed Forward Neural Network. …”
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Training method for a feed forward neural network based on meta-heuristics
Published 2018“…This paper proposes a Gaussian-Cauchy Particle Swarm Optimization (PSO) algorithm to provide the optimized parameters for a Feed Forward Neural Network. …”
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Neural Networks based fault diagnosis of ac motors
Published 2008“…The proposed ANN-based fault detector is developed using the Resilient Error Back Propagation (RPROP) training algorithm. The fast and reliable method for multilayer neural networks converges much faster than the conventional back propagation algorithm. …”
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Classification of agarwood using ANN / Muhammad Sharfi Najib ...[et al.]
Published 2012“…The network developed based on three layers feed forward network and the back propagation learning algorithm was used in executing the network training. …”
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Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network
Published 2014“…First, the best set of structures for feed forward neural network were found by multi objective parallel genetic algorithm. …”
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An intelligent optical fibre pH sensor based on sol-gel advanced material and artificial neural network / Mohd Nasir Taib, Faiz Bukhari Mohd Suah and Musa Ahmad
Published 2005“…The pH sensor is developed based on the use of bromophenol blue indicator immobilized in a sol-gel thin film as a sensing material. A three layer feed-forward network was used and the network training was performed using the back-propagation algorithm. …”
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Neural networks applied for fault diagnosis of AC motors
Published 2008“…The proposed ANN-based fault detector is developed using the Resilient Error Back Propagation (RPROP) training algorithm. The fast and reliable method for multilayer neural networks converges much faster than the conventional back propagation algorithm. …”
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20
Development of generalized feed forward network for predicting annual flood (depth) of a tropical river
Published 2014“…The governing training algorithm was back propagation with momentum term and tangent hyperbolic types was used as transfer function for hidden and output layers. …”
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