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Relevant bibliographies by topics / Gravimetry neural networks

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Academic literature on the topic 'Gravimetry neural networks'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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Journal articles on the topic "Gravimetry neural networks"

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Skiba, Marta, and Mariusz Młynarczuk. "Estimation of Coal’s Sorption Parameters Using Artificial Neural Networks." Materials 13, no. 23 (2020): 5422. http://dx.doi.org/10.3390/ma13235422.

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This article presents research results into the application of an artificial neural network (ANN) to determine coal’s sorption parameters, such as the maximal sorption capacity and effective diffusion coefficient. Determining these parameters is currently time-consuming, and requires specialized and expensive equipment. The work was conducted with the use of feed-forward back-propagation networks (FNNs); it was aimed at estimating the values of the aforementioned parameters from information obtained through technical and densitometric analyses, as well as knowledge of the petrographic composit

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TAVAKOLIPOUR, H., and M. MOKHTARIAN. "APPLICATION OF NEURAL NETWORK FOR ESTIMATION OF PISTACHIO POWDER SORPTION ISOTHERMS." Latin American Applied Research - An international journal 44, no. 3 (2014): 189–94. http://dx.doi.org/10.52292/j.laar.2014.440.

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Moisture sorption isotherms for pistachio powder were determined by gravimetric method at temperatures of 15, 25, 35 and 40ºC. Some mathematical models were tested to measure the amount of fitness of experimental data. The mathematical analysis proved that Caurie model was the most appropriate one. As well, adsorptiondesorption moisture content of pistachio powder were predicted using artificial neural network (ANN) approach. The results showed that, MLP network was able to predict adsorption-desorption moisture content with R2 values of 0.998 and 0.992, respectively. Comparison of ANN results

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Li, X. "Comparing the Kalman filter with a Monte Carlo-based artificial neural network in the INS/GPS vector gravimetric system." Journal of Geodesy 83, no. 9 (2008): 797–804. http://dx.doi.org/10.1007/s00190-008-0293-y.

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Tavakolipour, Hamid, and Mohsen Mokhtarian. "Estimation of Equilibrium Moisture Content of Pistachio Powder through the ANN and GA Approaches." International Journal of Food Engineering 10, no. 4 (2014): 747–55. http://dx.doi.org/10.1515/ijfe-2013-0022.

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Abstract In this study, two intelligent tools of genetic algorithm (GA) and artificial neural network (ANN) were employed to use experimental data to predict equilibrium moisture content (EMC) of Persian pistachio powder. Initially the moisture sorption isotherms of pistachio powder were determined by gravimetric method at different temperatures (15, 25, 35 and 40°C) and constant relative humidity’s (0.11, 0.23, 0.36, 0.49, 0.62, 0.75 and 0.88 aw values) and then traditional mathematical models including BET, Iglesias and Chirife, GAB, Caurie and Freundlich were used to check the fitness of ex

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Guo, Qiaofeng, Zhu Zhu, Zhen Cheng, Shuhong Xu, Xiaoliang Wang, and Yusen Duan. "Correction of Light Scattering-Based Total Suspended Particulate Measurements through Machine Learning." Atmosphere 11, no. 2 (2020): 139. http://dx.doi.org/10.3390/atmos11020139.

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Instruments based on light scattering used to measure total suspended particulate (TSP) concentrations have the advantages of fast response, small size, and low cost compared to the gravimetric reference method. However, the relationship between scattering intensity and TSP mass concentration varies nonlinearly with both environmental conditions and particle properties, making it difficult to make corrections. This study applied four machine learning models (support vector machines, random forest, gradient boosting regression trees, and an artificial neural network) to correct scattering measu

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Suntaro, Kiattisak, Supawan Tirawanichakul, and Yutthana Tirawanichakul. "Determination of Isosteric Heat and Entropy of Sorption of Air Dried Sheet Rubber Using Artificial Neural Network Approach." Applied Mechanics and Materials 541-542 (March 2014): 374–79. http://dx.doi.org/10.4028/www.scientific.net/amm.541-542.374.

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Equilibrium moisture contents (EMC) of air dried sheet (ADS) rubber were determined by commonly gravimetric-static method with saturated salt solution among surrounding temperatures of 40-70°C correlated to water activity (aw) ranges between 0.10 and 0.9. The experimental results was analyzed by 5 commonly EMC model. The results showed that equilibrium moisture content of ADS rubber decreased with increase of surrounding temperature at constant water activity and the simulated data using Chung-Pfost model has a good relation to experimental data with R2, RMSE and χ2 equal 0.9565, 0.0235 and 0.

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Isiyaka, Hamza Ahmad, Khairulazhar Jumbri, Nonni Soraya Sambudi, Zakariyya Uba Zango, Bahruddin Saad, and Adamu Mustapha. "Removal of 4-chloro-2-methylphenoxyacetic acid from water by MIL-101(Cr) metal-organic framework: kinetics, isotherms and statistical models." Royal Society Open Science 8, no. 1 (2021): 201553. http://dx.doi.org/10.1098/rsos.201553.

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Effective removal of 4-chloro-2-methylphenoxyacetic acid (MCPA), an emerging agrochemical contaminant in water with carcinogenic and mutagenic health effects has been reported using hydrothermally synthesized MIL-101(Cr) metal-organic framework (MOF). The properties of the MOF were ascertained using powdered X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, thermal gravimetric analysis (TGA), field emission scanning electron microscopy (FESEM) and surface area and porosimetry (SAP). The BET surface area and pore volume of the MOF were 1439 m 2 g −1 and 0.77 cm 3 g −1 , r

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Tekin, Yücel, Zeynal Tümsavas, and Abdul Mounem Mouazen. "Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy." Revista Brasileira de Ciência do Solo 38, no. 6 (2014): 1794–804. http://dx.doi.org/10.1590/s0100-06832014000600014.

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Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to ach

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Carpenter, Chris. "Machine-Learning Method Determines Salt Structures From Gravity Data." Journal of Petroleum Technology 73, no. 02 (2021): 70–71. http://dx.doi.org/10.2118/0221-0070-jpt.

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 201424, “Machine-Learning Method To Determine Salt Structures From Gravity Data,” by Jie Chen, Cara Schiek-Stewart, and Ligang Lu, Shell, et al., prepared for the 2020 SPE Annual Technical Conference and Exhibition, originally scheduled to be held in Denver, 5-7 October. The paper has not been peer reviewed. In the complete paper, the authors develop a machine-learning (ML) method to determine salt structures directly from gravity data. Based on a U-net deep neural network, the method maps the grav

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Gazor, Hamid Reza, and Afshin Eyvani. "Adsorption Isotherms for Red Onion Slices Using Empirical and Neural Network Models." International Journal of Food Engineering 7, no. 6 (2011). http://dx.doi.org/10.2202/1556-3758.2592.

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Moisture sorption isotherms of red onion slices were determined at 30, 40, 50, and 60°C using the standard gravimetric static method over a range of relative humidity from 0.11 to 0.83. The experimental sorption curves were fitted by seven empirical equations: modified Henderson, modified ChungPfost, modified Halsey, modified Oswin, modified Smith, modified BET, and GAB. Also three types of Artificial neural network models: linear, multilayer perceptron, and radial basis function were tested and developed to predict the equilibrium moisture content of onion slices and the selected models were

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Dissertations / Theses on the topic "Gravimetry neural networks"

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Maia, Túle Cesar Barcelos. "Utilização de redes neurais na determinação de modelos geoidais." Universidade de São Paulo, 2003. http://www.teses.usp.br/teses/disponiveis/18/18137/tde-19122003-185113/.

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A partir de dados obtidos do modelo do geopotencial EGM96, da gravimetria, do GPS e do nivelamento geométrico, e aplicando harmônicos esféricos e FFT como técnicas de determinação geoidal, foram utilizadas neste trabalho redes neurais artificiais como ferramenta alternativa na determinação de um modelo geoidal. Procurou-se uma determinação geoidal de forma mais rápida, com precisão adequada e com menor esforço na determinação de parâmetros importantes na obtenção da referida superfície. Foram utilizados modelos de redes neurais do tipo MLP, algoritmo de treinamento backpropagation, variando o

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Book chapters on the topic "Gravimetry neural networks"

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Yatsenko, V., D. Kruchinin, B. Vlahovic, I. Morozova, and S. Kruchinin. "Superconducting Gravimeters Based on Advanced Nanomaterials and Quantum Neural Network." In Advanced Nanomaterials for Detection of CBRN. Springer Netherlands, 2020. http://dx.doi.org/10.1007/978-94-024-2030-2_15.

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Conference papers on the topic "Gravimetry neural networks"

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Shimelevich, M. I., E. A. Obornev, I. E. Obornev, E. A. Rodionov, and D. A. Lyakhovets. "Formalized Inversion of Geophysical Data Using Neural Network Technologies with Application to the Tasks of Geoelectrics and Gravimetry." In Engineering and Mining Geophysics 2019 15th Conference and Exhibition. European Association of Geoscientists & Engineers, 2019. http://dx.doi.org/10.3997/2214-4609.201901717.

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