Search Results - back ((prediction algorithm) OR (selection algorithm))

Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending by Abu Khadra, Fayiz Y. M.

“…To validate the finite element model physical experiments were conducted. A neural network algorithm based on the backpropagation algorithm has been developed. …”
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Artificial neural network model with different backpropagation algorithms and meteorological data for solar radiation prediction by Heng S.Y., Ridwan W.M., Kumar P., Ahmed A.N., Fai C.M., Birima A.H., El-Shafie A.

“…article; artificial neural network; back propagation; conjugate; controlled study; Malaysia; prediction; relative humidity; solar radiation; wind speed; algorithm; Bayes theorem; meteorology; solar energy; Algorithms; Bayes Theorem; Meteorology; Neural Networks, Computer; Solar Energy…”

Prediction of optimum compositions of parenteral nanoemulsion system loaded with low solubility drug for treatment of schizophrenia by artificial neural network by Samiun, Wan Sarah, Basri, Mahiran, Masoumi, Hamid Reza Fard, Khairudin, Nurshafira

“…To obtain the optimum topologies, ANNs were trained by Incremental Back Propagation (IBP), Genetic Algorithm (GA), Batch Back Propagation (BBP), Quick Propagation (QP), and Levenberg-Marquardt (LM) algorithms for testing data set. …”
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Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm by Rehman Gillani, Syed Muhammad Zubair

“…This research proposed an algorithm for improving the current working performance of Back-propagation algorithm by adaptively changing the momentum value and at the same time keeping the ‘gain’ parameter fixed for all nodes in the neural network. …”
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Predicting the optimum compositions of a transdermal nanoemulsion system containing an extract of Clinacanthus nutans leaves (L.) for skin antiaging by artificial neural network mo... by Che Sulaiman, Intan Soraya, Basri, Mahiran, Masoumi, Hamid Reza Fard, Ashari, Siti Efliza, Basri, Hamidon, Ismail, Maznah

“…Five universal learning algorithms—incremental back propagation, batch back propagation, quick propagation, genetic algorithm, and Levenberg-Marquardt—were used in the ANN to achieve the optimum topologies. …”
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Modelling of elastic modulus degradation in sheet metal forming using back propagation neural network by M. R. Jamli, A. K. Ariffin, Dzuraidah Abd. Wahab

“…The method involves selecting the architecture, network parameters, training algorithm, and model validation. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…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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Early detection of dengue disease using extreme learning machine by Suhaeri, Suhaeri, Mohd Nawi, Nazri, Fathurahman, Muhamad

“…The result shows that the proposed ELM with selected clinical features can produce best generalization performance and can predict accurately with 96.94% accuracy. …”
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Modelling of Elastic Modulus Degradation in Sheet Metal Forming Using Back Propagation Neural Network by Jamli, Mohamad Ridzuan, Mohd Ihsan, Ahmad Kamal Ariffin, Abdul Wahab, Dzuraidah

“…The method involves selecting the architecture, network parameters, training algorithm, and model validation. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

“…Multiple cases are developed using different optimally selected input variable vectors to train and test the back propagation neural network (BP-NN) and the hybrid model. …”
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Wind power prediction using Artificial Neural Network: article by Edik, Septony

“…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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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…Multilayer Feedforward Back Propagation (MLFFBP) was used. Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
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Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

“…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. The researchers conducted the prediction of laser machining quality, namely surface roughness with seven significant parameters to obtain singleton output using machine learning techniques based on Quick Back Propagation Algorithm. …”
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Speaker verification based on speech signal by Shariffah Fauziah, Jap, Chekima, Ali, Mazlina, Mamat, Wan Mahani, Abdullah

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Oil palm maturity classifier using spectrometer and machine learning by Goh, Jia Quan

“…The prediction was able to produce 100% accuracies by using Linear and Weighted KNN as classification testing algorithm. …”
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Wind power prediction using Artificial Neural Network by Edik, Septony

“…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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Development of Artificial Neural Network (ANN) for lightning prediction under Malaysia environment / Jeremy AK Stewart Bedimbap by Stewart Bedimbap, Jeremy

“…In the proposed method, a three layer back-propagation neural network with Levenberg Marquardt algorithm has been developed and predicts the output data for the next four hours. …”
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Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih by Hashim, Asman

“…The research procedures chosen were the multi-layered perceptron with back propagation algorithmic learning. The research findings show that the most suitable predictive model comprises of eleven nodes in input-layer; five nodes in hidden-layer and one node in output-layer. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…Experimentally observed responses were used to train, map and optimize the network algorithms before the best architecture was selected. …”
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Improved recurrent NARX neural network model for state of charge estimation of lithium-ion battery using pso algorithm by Hossain Lipu M.S., Hussain A., Saad M.H.M., Ayob A., Hannan M.A.