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Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks
Published 2021“…For the validation of our claim, we implemented leukemia cancer classification task and compared our method with standard BPMLP method. The proposed FBP-MLP method outperformed the conventional BP-MLP algorithm both in terms of convergence rate and test accuracy. …”
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A multi-layer perceptron for scheduling cellular manufacturing systems in the presence of unreliable machines and uncertain cost
Published 2016“…To solve the proposed problem, a number of metaheuristics are developed including Branch and Bound; Simulated Annealing algorithms; Fuzzy Art Control; Ant Colony Optimization and a hybrid Multi-layer Perceptron and Simulated Annealing algorithms. …”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…The recognition rate is presented and compared with another related research work, where the results show equal performance of both algorithms. This shows that machine-learning algorithm such as MLP is a viable method for color segmentation as well as object recognition.…”
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Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction
Published 2012“…The proposed KGA model combines greedy algorithm withk-means++ clustering in this research to assist users in automating the finding of the optimal number of new-ons inside the hidden layer of the BP network. …”
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Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm
Published 2023“…Complex networks; Drops; Forecasting; Iterative methods; Network architecture; Network layers; Optimization; Rivers; Stochastic models; Stochastic systems; Stream flow; Time series; Engineering applications; Gradient-decent algorithm; Intelligent Water Drops (IWD); Multi layer perceptron; Multi-layer perceptron neural networks; Optimization algorithms; Streamflow forecasting; Time series prediction; Multilayer neural networks…”
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System identification of hammerstein model a quarter car passive suspension systems using Multilayer Perceptron Neural Networks (MPNN)
Published 2005“…The Network Learning Algorithm Is Based On Fisher’s Scoring Method. Fisher Information Is Given As A Weighted Covariance Matrix Of Inputs And Outputs Of The Network Hidden Layer. …”
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Genetic algorithms-based quality of service service selection in cloud computing using multilayer perceptron
Published 2014“…The attribute selection method is based genetic algorithms (GA) and is designed to rank the cloud services before the attributes are being fed into a multi-layer perceptron (MLP) classification system. …”
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Performance of Levenberg-Marquardt neural network algorithm in air quality forecasting
Published 2022“…Levenberg-Marquardt algorithm and conjugate gradient method are frequently used for optimization in multi-layer perceptron (MLP). …”
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Performance of Levenberg-Marquardt neural network algorithm in air quality forecasting
Published 2022“…Levenberg-Marquardt algorithm and conjugate gradient method are frequently used for optimization in multi-layer perceptron (MLP). …”
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Identification algorithms of flexible structure using neural networks
Published 2006“…Furthermore, non-parametric models of the system are developed using Multi-layer Perceptron Neural Networks (MLP-NN) and Elman Neural Networks (ENN). …”
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A new soft computing model for daily streamflow forecasting
Published 2023“…Climate change; Data streams; Floods; Forecasting; Genetic algorithms; Hydroelectric power plants; Mean square error; Multilayer neural networks; Particle swarm optimization (PSO); Soft computing; Soil conservation; Water conservation; Water management; Water supply; Flow quantification; Multi layer perceptron; Optimization algorithms; Predicting models; Root mean square errors; Soft computing models; Streamflow forecasting; Watershed management; Stream flow; algorithm; forecasting method; hydroelectric power plant; numerical model; optimization; principal component analysis; streamflow; watershed; Helianthus…”
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Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…The standard learning method for tuning weights in FLNN is Backpropagation (BP) learning algorithm. …”
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Hybrid multilayered perceptron network for classification of bundle branch blocks
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Forecasting particulate matter concentration using linear and non-linear approaches for air quality decision support
Published 2023“…Air quality; Decision support systems; Fog; Forecasting; Functions; Linear regression; Nonlinear systems; Particles (particulate matter); Radial basis function networks; Forecasting algorithm; Forecasting performance; Malaysia; Multi layer perceptron; Multiple linear regressions; Particulate Matter; Radial basis functions; Urban and rural areas; Urban growth; air quality; algorithm; decision support system; early warning system; forecasting method; multiple regression; particulate matter; performance assessment; precision; Malaysia; West Malaysia…”
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Identification algorithms of flexible structure using neural networks
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Computationally efficient single layer transformer convolutional encoder for accurate price prediction of agriculture commodities
Published 2025“…Therefore, this study introduces the single-layer Transformer Convolutional Encoder algorithm (STCE), an improved version of the traditional transformer encoder. …”
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