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Cited by 48 publications
(15 citation statements)
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References 47 publications
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“…Hence, the results proved that Bayesian Regularization gave better results as compared with the other two approaches. is finding is similar to [28,50] but different from [33]. GSD faces heterogeneous work environments that results in multiple challenges which have been highlighted in this research study.…”
Section: Discussionmentioning
confidence: 56%
See 1 more Smart Citation
“…Hence, the results proved that Bayesian Regularization gave better results as compared with the other two approaches. is finding is similar to [28,50] but different from [33]. GSD faces heterogeneous work environments that results in multiple challenges which have been highlighted in this research study.…”
Section: Discussionmentioning
confidence: 56%
“…In [ 49 ], authors applied these three ANN techniques for the prediction of Flash Floods and found Bayesian Regularization an efficient technique as compared with the other two techniques. Authors in [ 50 ] used ANN for reservoir petro-physical properties such as porosity, permeability, and water saturation. In [ 51 ], authors compared relative predictive abilities of Levenberg–Marquardt and Bayesian Regularization methods for data on prices of four cryptocurrencies, namely, Bitcoin, Bitcoin Cash, Litecoin, and Ripple and found that the Bayesian Regularization method gives less error in prediction as compared with Levenberg–Marquardt in case of large data but both the methods are found nearly equally efficient for small data.…”
Section: Artificial Neural Networkmentioning
confidence: 99%
“…To decide on the final model, the RMSE, ADD, and R 2 values were comparatively analyzed for the topologies of QP-4-4-1, IBP-4-7-1, BBP-4-7-1, GA-6-14-1, and LM-4-5-1. Furthermore, to determine the R 2 values, the topologies projection and actual values of the D p were plotted for the testing data group [56] (Fig. 2).…”
Section: Model Selectionmentioning
confidence: 99%
“…By estimating the fluid types and their volume as well as the rock and mineral types, petrophysical studies will help to provide comprehensive information about the reservoir. Therefore, in various types of research studies, including reservoir characterization [5][6][7][8][9][10][11][12][13], hydraulic fracturing simulation/operation [14][15][16][17][18][19][20][21][22][23], and building, evaluating, and controlling numerical models [24,25], petrophysical parameters play a vital role. Porosity, permeability, and water saturation, which are considered as three main reservoir petrophysical properties, are provided by core or well-logging data.…”
Section: Introductionmentioning
confidence: 99%