artificial neural network parameters
Prediction and Optimization of Blast Furnace Parameters using Artificial Neural Network
... branches, neural networks are ...approach. Neural networks can be used for all areas predictive, classification or control-related ...building artificial neural networks ...
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Optimization of EDM Process Parameters by Using Artificial Neural Network: A Review
... A neural network is generally mathematical algorithm based technique. In this technique it modulate the operation of bio-logical neural system. In 1943, McCulloch and Pitts developed the technique ...
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1. Kernel network parameters optimization using optimized artificial neural network to serve quality of service parameters
... A TCP window of data is the amount of data transmitted on a connection during one round-trip time. The concepts regarding various TCP windows used here, is explained below. Receive window: is the buffer amount as ...
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Osmotic Drying Rate Estimation for Dehydration of Beetroot Slices using Artificial Neural Network
... develop Artificial Neural Network model that will correlate the dependent parameters, the weight loss and drying rate, with temperature, concentration of salt solution and time for osmotic ...
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Applying ANN, ANFIS, and LSSVM Models for Estimation of Acid Solvent Solubility in Supercritical CO
... process. Artificial neural network has ability of tracing a nonlinear form relationship between input and output ...ability, artificial neural networks have widespread application in ...
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Study on Pollution Forecasting using 2Phase Neural Network
... Artificial Neural Network for Pollution Forecasting : Forecasting it is intuitive that accuracy is very important ...input parameters for a pollution forecasting model are different different ...
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Title: CLASSIFICATION ON BREAST CANCER USING GENETIC ALGORITHM TRAINED NEURAL NETWORK
... Abstract— Artificial neural networks have been in the position of producing complex dynamics in control applications over the last decade, especially when they are linked to ...for network design, ...
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Vol 5, No 1 (2013)
... on artificial intelligence algorithms. Neural network optimization based on three basic parameters topology, weights and the learning rate is a powerful ...the network structure and ...
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CALCULATION OF MICROSTRIP PATCH ANTENNA PARAMETERS USING ARTIFICIAL NEURAL NETWORK.
... antenna parameters returns loss, VSWR and directivity between using HFSS Software and Artificial Neural ...ANN network are compared with the data obtained from HFSS software and concluded that ...
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Application of Artificial Intelligence for Epilepsy Disease
... hyper- parameters may be adjusted for most favorable instruction ...recurrent Neural Network (RNN) ...belief network [11] and restricted Boltzmann machine [10], in short it is written DBN and ...
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Optimization of underwater wet welding process parameters using neural network
... the neural network should ideally be able to learn and understand the interaction between the welding process ...the network because it is suitable for the training of larger ...In artificial ...
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Informative Feature Trained Classification System For Credit Card Fraud Detection
... Neural network based fraud detection methods are most ...of artificial neurons is contained in artificial neural ...of neural network. In neural network ...
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Neural Network Priority Use of BTS for Optimizing Telecommunications in Indonesia
... designing Artificial Neural Network modeling system which will be used to determine and recognize the pattern in predicting the villages becoming the priority of installation of BTS USO for ...
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NeuroSVM: A Graphical User Interface for Identification of Liver Patients
... feed-forward artificial neural network ...statistical parameters like root mean square error (RMSE) and mean absolute percentage error ...
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Non linear algorithm analysis of large scale traffic data for systematic pattern detection
... an artificial neural network (ANN) model has been choose to estimate the data, which have been lost in the Federal Highway Kuala Lumpur when Automatic Incident Detection (AID) devices had not been ...
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Improved the Prediction of Multiple Linear Regression Model Performance Using the Hybrid Approach: A Case Study of Chlorophyll a at the Offshore Kuala Terengganu, Terengganu
... an Artificial Neural Network to the MLR coins as Artificial Neural Network- Multiple Linear Regression ...(MLR), Artificial Neural Network (ANN) and proposed ...
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Review on Transformer Protection through Arti...
... an artificial neuron on computer that closely matches a biological neuron is given by an op-amp summer-like ...The artificial neuron is also called a processing element, a neurode, a node, or a ...
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Disease Identification in Cotton Plants Using Spatial FCM & PNN Classifier
... Santanu &Jaya described a software prototype system in paper for disease detection based on the infected images of various rice plants. They used image growing, image segmentation techniques to detect infected parts ...
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Radio location of partial discharge sources : a support vector regression approach
... RBF network architecture used for PD localisation consist of three inputs, corresponding to the RSS measurement data from the three sensors, a hidden layer and an output layer with two neurons, representing PD ...
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Prediction of prostate cancer by deep learning with multilayer artificial neural network
... in artificial intelligence are now being applied to various fields in society and ...A neural network simulates the pattern recognition capabilities of a biological ...multilayer artificial ...
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