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[PDF] Top 20 Modeling Distillation Column Using ARX Model Structure and Artificial Neural Networks

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Modeling Distillation Column Using ARX Model Structure and Artificial Neural Networks

Modeling Distillation Column Using ARX Model Structure and Artificial Neural Networks

... [r] ... See full document

6

Photovoltaic power forecast modeling with artificial neural networks

Photovoltaic power forecast modeling with artificial neural networks

... forecast structure based on a grid-connected photovoltaic system in the University of ...forecast structure is composed of two non-linear dynamic forecasting models and one non-linear static ... See full document

102

Prediction of Electrochemical Machining Process Parameters using Artificial Neural Networks

Prediction of Electrochemical Machining Process Parameters using Artificial Neural Networks

... Artificial neural networks (ANNs), as one of the most attractive branches in artificial intelligence, has the potential to handle problems such as modeling, estimating, prediction, ... See full document

8

Application of multivariable control using artificial neural networks in a debutanizer distillation column

Application of multivariable control using artificial neural networks in a debutanizer distillation column

... on neural identification of a mutivariable input- mutivariable output (MIMO) ...debutanizer column. Debutanizer distillation column is used to remove the litht components from the gasoline ... See full document

1

Clinics  vol.65 número12

Clinics vol.65 número12

... examiners using the acquisition protocol recommended by the ...alignment and a cornea fit zone of 9 mm were applied for best-fit spheres in all ...maximum and minimum simulated keratometry, index of ... See full document

6

J. Microw. Optoelectron. Electromagn. Appl.  vol.12 número1

J. Microw. Optoelectron. Electromagn. Appl. vol.12 número1

... lobe levels are controlled with taking in to account the non-uniform current excitations and applying phase shifts. Antenna characteristics are determined by geometrical position of radiators, amplitude and ... See full document

7

Assessment of earthquake-triggered landslide susceptibility in El Salvador based on an Artificial Neural Network model

Assessment of earthquake-triggered landslide susceptibility in El Salvador based on an Artificial Neural Network model

... techniques using the same input data, and the results illustrated the importance of terrain roughness and soil type as key factors within the model; using only these two variables, the ... See full document

9

Bankaların Finansal Başarısızlıklarının Geleneksel ve Yeni Yöntemlerle Öngörüsü(Prediction of Financial Failure of Banks with Traditional and New Methods)

Bankaların Finansal Başarısızlıklarının Geleneksel ve Yeni Yöntemlerle Öngörüsü(Prediction of Financial Failure of Banks with Traditional and New Methods)

... boyutlu model çalışmalarına ise aşağıdaki örnekler verilebilir: Altman (1968), çalışmasında çok değişkenli istatistik analiz yöntemi olan “çoklu diskriminant analizini” ... See full document

15

Hybrid artificial intelligence algorithms for short-term load and price forecasting in competitive electric markets

Hybrid artificial intelligence algorithms for short-term load and price forecasting in competitive electric markets

... When using WT an important decision has to be made: the selection of a suitable mother wavelet, in the particular STLF case, the choice of Daubechies family wavelets is almost consensual, with special emphasis on ... See full document

111

Modeling brain resonance phenomena using a neural mass model.

Modeling brain resonance phenomena using a neural mass model.

... magneto- and electro- encephalography (M/EEG), local field potentials (LFP) or single unit recordings contain rich information on brain function, which may be related to specific cognitive processes, to general ... See full document

17

Deep learning model combination and regularization using convolutional neural networks

Deep learning model combination and regularization using convolutional neural networks

... convolution neural network, known as the Neocognitron, was proposed by Fukushima [Fuk80, Fuk86b] and originally applied to the problem of handwritten digit ...cortex structure of mammals, proposed by ... See full document

72

Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.

Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.

... values, and S&P 500 daily index ...ARIMA, and Radial Basis Function Neural Networks (RBFN) to forecast the price of electricity in Spain by treating the price behavior as a nonlinear ... See full document

23

Neural Network Based 3D Surface Reconstruction

Neural Network Based 3D Surface Reconstruction

... diffuse and specular components of the reflectance model simultaneously has been ...Two neural networks with symmetric structures were used to estimate these two components separately ... See full document

6

Modeling and simulation of Polymer Composite laminate bolted Joint

Modeling and simulation of Polymer Composite laminate bolted Joint

... composite and cost effective option to synthetic fiber reinforced ...the modeling and simulation of bearing properties of hybrid fiber polymer composite mechanical joint using ... See full document

7

Towards Development of Real-Time Handwritten Urdu Character to Speech Conversion System for Visually Impaired

Towards Development of Real-Time Handwritten Urdu Character to Speech Conversion System for Visually Impaired

... recognition using multilayer feed forward neural network reporting an accuracy of ...Markov Model (HMM)-based speech synthesis and waveform-based speech synthesis to develop human like ... See full document

7

EMPREGABILIDADE DE REDES NEURAIS ARTIFICIAIS (RNA) NA PREDIÇÃO DA QUALIDADE DE PAINÉIS AGLOMERADOS

EMPREGABILIDADE DE REDES NEURAIS ARTIFICIAIS (RNA) NA PREDIÇÃO DA QUALIDADE DE PAINÉIS AGLOMERADOS

... technical and economic implications for wooden products since costs can reach up to half of the product total price (CARNEIRO et ...machines and easy handling (ROFFAEL; SCHNEIDER, ...fruits and seeds ... See full document

10

Composition control of a binary distillation column using multivariable optimal control

Composition control of a binary distillation column using multivariable optimal control

... [r] ... See full document

22

Estimation of flood warning runoff thresholds in ungauged   basins with asymmetric error functions

Estimation of flood warning runoff thresholds in ungauged basins with asymmetric error functions

... 0.3 and 0.4, but they are all still very close to the zero-error line and, correctly, their position shifts upwards with increasing asym- metry, so that for α = ... See full document

31

High-efficiency phenotyping for vitamin A in banana using artificial neural networks and colorimetric data

High-efficiency phenotyping for vitamin A in banana using artificial neural networks and colorimetric data

... network and 30%, for validation (18 ...training and validation fractions were randomly ...(MLP) networks were used for the analysis and developed using the “mlp” function of the RSNNS ... See full document

7

RECENT METHODS FOR OPTIMIZATION OF PLASTIC INJECTION MOLDING PROCESS –A RETROSPECTIVE AND LITERATURE REVIEW

RECENT METHODS FOR OPTIMIZATION OF PLASTIC INJECTION MOLDING PROCESS –A RETROSPECTIVE AND LITERATURE REVIEW

... Artificial neural networks (ANNs) are defined as mathematical models which represent the biological process of a human ...interconnections, and learning rules ...receives and processes ... See full document

15

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