Multilayer Perceptron Artificial Neural Networks
Representing intelligent decision making in discrete event simulation : a stochastic neural network approach
... [Keywords: Discrete Event Simulation, Neural Networks, Multilayer Perceptron, Artificial Intelligence, Behaviour, Decision Making, Intelligent Agents, Stochastic Processes]... Discrete e[r] ...
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Application of Artificial Neural Network and Adaptive Neural based Fuzzy Inference System Techniques in Estimating of Virtual Water
... techniques, Multilayer Perceptron (MLP), Radial Basis Functions (RBF), and Generalized Regression Neural Networks (GRNN) as well as ANFIS were examined in estimation of VW using measured data ...
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Short-term prediction of NO2 and NOx concentrations using multilayer perceptron neural network: a case study of Tabriz, Iran
... Artificial neural networks (ANNs) are able to approxi- mate accurately complicated nonlinear input–output re- lationships. Like their physics-based numerical model counterparts, ANNs require training ...
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System identification of hammerstein model a quarter car passive suspension systems using Multilayer Perceptron Neural Networks (MPNN)
... The neural network developed in this research is used to identify the nonlinear model of a quarter car passive suspension system. The car model is derived using Hammerstein model. The Hammerstein cascade can be a ...
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Prediction of the pharmaceutical solubility in water and organic solvents via different soft computing models
... different artificial neural networks, including multilayer perceptron, radial basis function, and support vector machine, were constructed to predict the solubility of these different ...
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Efficiency of Multilayer Perceptron Neural Networks Powered by Multi Verse Optimizer
... of artificial neural networks (ANNs) have considerable power to solve problems in wide range of ...the perceptron, as a building block, sophisticated structures of ANNs can be ...
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Comparative Application of Radial Basis Function and Multilayer Perceptron Neural Networks to Predict Traffic Noise Pollution in Tehran Roads
... the neural network model to pre- dict the noise levels due to continuous and non- continuous traffic flow in ...back-propagation neural network (BPN) and a regression model to predict the noise of ...
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Implementation of Artificial Neural Networks and Decision Tree Algorithms for Heart Disease Diagnosis
... The data was collected from the patients’ heart disease data sets. The preprocessing technique was applied to the dataset to reduce the noise from data, transform the format of the data, and remove the irrelevant ...
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ANNIDS: Artificial Neural Network based Intrusion Detection System for Internet of Things
... that Artificial Neural Network (ANN) provides better accuracy and detection rate than other ...an Artificial Neural Network based IDS (ANNIDS) technique based on Multilayer ...
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Numerical Solution of Sixth Order Differential Equations Arising in Astrophysics by Neural Network
... Hopfield neural network ...forward neural network. Artificial neural networks based on Broyden-Fletcher-Goldfarb-Shanno (BF GS) optimization technique for solving ordinary and partial ...
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Gait Recognition Using Deep Learning
... Neural networks are predictive models loosely based on the action of biological ...name, neural networks are far from “thinking machines” or “artificial ...artifical neural ...
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APPLICATION OF MULTILAYER PERCEPTRON BASED ARTIFICIAL NEURAL NETWORK FOR MODELING OF RAINFALL RUNOFF IN A HIMALAYAN WATERSHED
... different artificial neural network (ANN) models, multi layer feed-forward neural network using Levenberg–Marquardt learning algorithm (LMFF) and radial basis function (RBF) models for predicting ...
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Detection of mastitis and its stage of progression by automatic milking systems using artificial neural networks
... of artificial neural networks, multilayer perceptron (MLP) and self-organizing feature map (SOM) were used to detect mastitis by automatic milking systems (AMS) using a new mastitis ...
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Title: AN EFFICIENT MODEL FOR SEASONAL PREDICTABILITY ON NORTH EAST MONSOON USING MULTILAYER PERCEPTRON
... websites. Artificial Neural Networks is a very admired and one of the most widely used techniques for rainfall ...forecasting. Multilayer Perceptron algorithm is used to predict the ...
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Reducing Error Signal in Multilayer Perceptron Neural Networks using MLP for Label Ranking
... true perceptron performs binary classification, a neuron in a multilayer perceptron is free to either perform classification or regression, depending upon its activation ..."multilayer ...
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EMBEDDING RАPIDMINER MODELS IN JAVA CODE
... two neural network models one is an Multilayer Perceptron Neural Network with sigmoidal activation function and the other is a Radialbasis function network with Gaussian function as the ...
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Artificial Intelligence in the Estimation of Patch Dimensions of Rectangular Microstrip Antennas
... MLP neural network is trained using learning rules namely Levenberg-Marquardt (LM), Scale Conjugate Gradient Back propagation (SC- GBP), Gradient of Fletcher Reeves algorithm (GFR), Quasi Newton algorithm (QN), ...
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Prediction of the Experimental Data for Removal of Organic Pesticides by Carbon Nanoparticle Synthesized from Pomegranate Peel using Artificial Neural Networks
... of Neural Information Processing Systems (NIPS) ...testing neural networks using previous data not used in the training of network ...two-layer neural network consisting of a hidden layer of ...
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Prediction of prostate cancer by deep learning with multilayer artificial neural network
... Results: With any prostate cancer objective variable, Lasso and stepwise regression analyses selected 12 and nine explanatory variables from 22, respectively. Using trained ANNs with multiple hidden layers, the accuracy ...
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A GENETIC ALGORITHM OPTIMIZED MULTI-LAYER PERCEPTRON FOR SOFTWARE DEFECT PREDICTION
... Most broadly utilized neural network model for classification is MLP in light of one or all the more consecutively joined layers of perceptron. MLP model considered in this paper fits in with the feed ...
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