[PDF] Top 20 Artificial neural network for traffic noise modeling
Has 10000 "Artificial neural network for traffic noise modeling" found on our website. Below are the top 20 most common "Artificial neural network for traffic noise modeling".
Artificial neural network for traffic noise modeling
... vehicular traffic noise is considered one of the most invasive type of pollution and often the most intrusive of ...of noise pollution modelling varies from the smart result of classic regressive ... See full document
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Modeling of Relative Humidity Using Artificial Neural Network
... feedforward artificial neural network ...the neural networks. Based on results, the proposed neural network gives accurate prediction of hourly relative humidity whereas the ... See full document
7
Evaluation of Ultimate Torsional Strength of Reinforcement Concrete Beams Using Finite Element Analysis and Artificial Neural Network
... for modeling of complicated, highly nonlinear and ambiguous phenomena, artificial neural networks (ANN) are appropriate ...the artificial neural network is used for achieving ... See full document
8
Artificial neural network modeling of p-cresol photodegradation
... the network for testing data versus of the number of neurons in the hidden layer using IBP, QP, BBP and LM ...the network with 8 hidden neurons produced the best performances when IBP algorithm was ...The ... See full document
7
Modeling Gold Price via Artificial Neural Network
... The rest of the paper is organized as follows: Section II summarizes artificial neural networks. Section III describes the ARIMA model, including the determination of the orders of ARMA model. Section IV ... See full document
5
Modeling of Speech Recognition Using Artificial Neural Network
... with Neural Network. In this Neural Network toolbox of MATLAB R2015a has been ...of neural network, Feedforward with backpropagation and the Radial basis functions are executed ... See full document
5
Research on Classification of E-shopper Based on Neural Networks and Genetic Algorithm
... of modeling dynamic architecture for artificial neural networks (ANN) and a novel machine-learning algorithm for extracting rules from databases via using genetic ... See full document
8
Fuzzy Artificial Neural Networks and Particle Swarm Optimization Based Enhanced Traffic Signal Controlling System
... fuzzy artificial neural network (FANN) is a hybrid intelligent system that possesses the capabilities to adjust adaptively and intelligent processing of ...in neural network research ... See full document
6
Modeling of a Glass Tank Furnace Using Artificial Neural Network
... Abstract: Modeling of an Industrial side port regenerative glass tank furnace for float glass manufacturing has been done using a Radial Basis Function (RBF) neural network to connect various input ... See full document
6
Analysis of cardiovascular (cvd)/coronary heart diseases(chd) using artificial neural network (ann)
... ANN configuration and Back-Propagation Algorithm (Levenberg –Marquardt (LM) algorithm): In the present study a feed forward back propagation ANN is configured for the classification and recognition of ... See full document
8
Artificial Neural Network Modeling of Job Satisfaction: A Case Study of ICT, Federal University of Agriculture, Makurdi
... network architecture for predicting job satisfaction. Result indicated that the predicted values of job satisfaction were in the range of 1.42 – 2.00 as compared with the actual values of 1.50 – 2.00 obtained from ... See full document
6
Artificial Neural Network Classification for Gunshot Detection and Localization System
... Fig 3:- Experimental set-up for recording M16 gunshot Microphones were used as primary sensors. Sound signal properties were used to identify or differentiate gunshot from background noise and other explosive ... See full document
5
Quantitative Structure-Pharmacokinetic Relationships: artificial neural network modeling
... With the increasing number of theoretical descriptors able to be generaled from drug structure, GNNs have also successfully aided the selection of key descriptors for QSPR models constru[r] ... See full document
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Applying Fuzzy Logic Model for Bending Rigidity Evaluation of Woven Fabrics
... regression, artificial neural network model, ...three modeling methodologies based on mathematical, empirical and artificial neural network was ... See full document
8
Prediction of Drug Lipophilicity Using Back Propagation Artificial Neural Network Modeling
... STATISTICA Neural Networks software. Back propagation is the best known training algorithm for neural networks, and still one of the most useful. Back-propagation is a gradient descent on the error surface, ... See full document
10
Higher Order Fitting based Image De-noising using ANN
... This paper proposes a technique that uses Artificial Neural Network as its base because of its adaptive learning feature. In this method we will load the image from the database and then add ... See full document
7
Developing an artificial neural network for modeling and prediction of temporal structure and spectral composition of environmental noise in cities
... based noise classifier ...ambient noise frequency ...the noise source, according to the characteristics given by the ...automatic noise recognition are presented in (Betkowsa et ...based ... See full document
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ANN based short-term traffic flow forecasting in undivided two lane highway
... term traffic forecasting is one of the important fields of study in the transporta- tion ...term traffic forecasting is very useful to develop a more advanced transportation system to control traffic ... See full document
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Traffic Control on Cruise Ships for Autonomous Vehicles Applying Artificial Neural Network
... The Artificial Neural Networks, from their origin, are oriented to solve problems in the same way as the human brain ...Neuronal Artificial Network of multilayer perceptron type (PMC) for the ... See full document
5
Machine learning approach for detection of nonTor traffic
... of Artificial neural network (ANN) and Support vector machines (SVM) in terms of overall accuracy in detecting nonTor traffic in a Tor network traffic dataset data from the ... See full document
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