two-hidden-layer neural network
Development and Evaluation of A Comprehensive Greenhouse Climate Control System Using Artificial Neural Network
... Three-layer neural network with two feedbacks from hidden layers and delay in input provided a better description of relative humidity and light ...forward neural network ...
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Classification Using Two Layer Neural Network Back Propagation Algorithm
... the network the network topology is described by specifying the number of units in input layer, hidden layer and output ...Input layer is not counted and hidden ...
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A constraint based random search algorithm for optimizing neural network architectures and ensemble construction in detecting loss of coolant accidents in nuclear power plants
... optimizing neural network (NN) architectures and ensemble construction in three stages for detecting the break size of an IH of a ...2-hidden layer, 3-hidden layer and 4-hiddden ...
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Predicting the Daily Efficiency of Tehran Stock Share Price by Using of Artificial Neural Networks, Cascade Forward
... designed neural networks, the neural network with the feed forward cascade architecture and five input parameters, two hidden layer and 6 hidden node (with a 5-6-1 ...
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Spurious Valleys in One-hidden-layer Neural Network Optimization Landscapes
... one-hidden-layer neural networks, with a hidden layer of size p, and covers both empirical and population risk ...define two quantities depending on the functional space spanned ...
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Development of a Neural-Networks Tool-Wear Monitoring System for a Turning Process
... the hidden layer was determined by experiments comparing the network performances with a different number of neurons in the hidden ...with two to seven neurons in the hidden ...
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LONG TERM LOAD FORECASTING OF POWER SYSTEMS USING ARTIFICIAL NEURAL NETWORK AND ANFIS
... the neural network has two-layer feed-forward network with sigmoid hidden neurons and linear output neurons and also used for training with Leven Berg-Marquardt backpropagation ...
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Artificial Intelligence for Speech Recognition Based on Neural Networks
... a network structure determines the features of neural ...multilayer neural networks direct action or layered ...previous layer. Minimum implementation is smiling two-layer ...
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The Impact of the Neural Network Structure by the Detection of Undesirable Network Packets
... a neural network with one hidden layer (3 layer neural network) and a sufficient number of hidden neurons, capable of simulating each binary or continuous function ...
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Enhancing recurrent neural network-based language models by word tokenization
... the network are the previous n-words according to the language models ...projection layer. The hidden layer output is com- puted using Tanh function ...final network output is computed ...
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Neural networks in geophysical applications
... Other interesting preprocessing techniques to reduce input can be found in Almeida (1994). All of these are cast in the form of neural networks structures. Notice, however, that nearly always the individual ...
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Research and application of the combined model of principal component analysis and neural network based on SPSS
... Propagation) neural network is the study process of error back propagation algorithm which is made up of information forward propagation and error back ...input layer are responsible for receiving ...
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Training Continuous Space Language Models: Some Practical Issues
... the network (Bilmes et ...estimate neural language models on very large cor- pora; it has also been observed empirically that sam- pling the training data can increase the generaliza- tion performance ...
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Neural Network for the Prediction of Retrofitting/Reconditioning/Upgradation cost of CNC Machines
... CNC system refers to the automation of machine tools that are operated by abstractly programmed commands encoded on storage medium, as opposed to manually controlled. In Manufacturing sectors like power equipment ...
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Prediction of Seismic zone in India using Neural Network Algorithms
... G. Asencio-Corte´s et al., (2015) proposed the EQP-ANN model for the forecast of earthquakes of various scale magnitude in Tokyo town with five successive datasets for the year 2015. The earthquakes with the magnitude ...
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Prediction of Methane Fraction in Biogas from Landfill Bioreactors by Neural Network Modeling
... modeling, neural network- based (NN) models have been applied to predict various pollutant ...tree layer NN model with a hidden recurrent layer to predict SO2 concentration at three ...
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Investigation of Wireless Sensor Network Node Localization with Reduced Power Consumption
... of two estimating distance methods was given with their simulations and ...deployed network was achieved by, Talib [5], by scheduling the impacts of transmission, reception and sleep states on the energy ...
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Determination of Minimum Miscibility Pressure in Gas Injection Process by Using ANN with Various Mixing Rules
... a neural networks concept for prediction of MMP in a gas injection process and establish a proper relation between independent and dependent ...artificial neural network was used before while some ...
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Radial basis function neural network for software engineering measures A survey
... of Neural Network, and contains a unique hidden ...Output layer of PSN contains the product units whereas the hidden layer contains the summing ...input layer and ...
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Combination of Multiple Neural Networks to Solve Travelling Salesman Problem using Genetic Algorithm
... multiple neural networks to find the final ...artificial neural network. An algorithm for combining multiple neural networks was ...mutual neural networks with the use of genetic ...
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