The improvement of wavelet-based multilinear regression for suspended sediment load modeling by considering the physiographic characteristics of the watershed [PDF]
Water Science and Technology, 2023 The aim of this study is to model a relationship between the amount of the suspended sediment load by considering the physiographic characteristics of the Lake Urmia watershed. For this purpose, the information from different stations was used to develop
Niloofar Nejatian +4 more
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Prediction of Retention Indices and Response Factors of Oxygenates for GC-FID by Multilinear Regression [PDF]
Data, 2022 The replacement of fossil carbon sources with green bio-oils promotes the importance of several hundred oxygenated hydrocarbons, which substantially increases the analytical effort in catalysis research. A multilinear regression is performed to correlate
Nils Kretzschmar +3 more
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Ratios determining of microenterprise profitability: an analysis based on multilinear regression models [PDF]
Data and MetadataIntroduction: to determine the best multilinear regression model(s) of the Return on Assets and the Return on Equity of microenterprises in the commune of San Bernardo de Santiago de Chile; to strengthen their competitiveness in the industry, contributing to the strengthening of public policy in the sector, the source of information was the Mayor's ...
Luis Pedro Román Palma +3 more
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Modeling Soil Moisture from Multisource Data by Stepwise Multilinear Regression: An Application to the Chinese Loess Plateau [PDF]
ISPRS International Journal of Geo-Information, 2021 This study aims to integrate multisource data to model the relative soil moisture (RSM) over the Chinese Loess Plateau in 2017 by stepwise multilinear regression (SMLR) in order to improve the spatial coverage of our previously published RSM. First, 34 candidate variables (12 quantitative and 22 dummy variables) from the Moderate Resolution Imaging ...
Lina Yuan +6 more
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Recurrence Multilinear Regression Technique for Improving Accuracy of Energy Prediction in Power Systems [PDF]
EnergiesThis paper demonstrates how artificial intelligence can be implemented in order to predict the energy needs of daily households using both multilinear regression (MLR) and single linear regression (SLR) methods.
Quota Alief Sias +3 more
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Road Traffic Noise Predictions by means of L10 Modelling with a Multilinear Regression Calibrated on Simulated Data [PDF]
International Journal of Mechanics, 2023 Estimation of road traffic noise is fundamental for the health of people living in urban areas, and it is usually assessed based on field-measured data. Real data may not always be available, anyway, and for this reason, predictive models play an important role in the evaluation and controlling of the noise impact.
Rossi D., Mascolo A., Guarnaccia C.
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The Use of Multilinear Regression Models in Patterned Waterfloods: Physical Meaning of the Regression Coefficients [PDF]
, 2005 One of the reservoirs engineer's mission is to predict the behavior of hydrocarbon producing assets. Once this ability is developed he/she will try to manage tbe ''today" to maximize the future economic return of the asset. However, the techniques to predict future performance vary from an educated guess of an appropriate analogy to very complex ...
Gentil, Pablo Hugo
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Artificial Neural Network and Regression Models for Predicting Intrusion of Non-Reacting Gases into Production Pipelines [PDF]
Energies, 2022 Wax deposition and gelation of waxy crude oil in production pipelines are detrimental to crude oil transportation from offshore fields. A waxy crude oil forms intra-gel voids in pipelines under cooling mode, particularly below the pour point temperature.
Girma Tadesse Chala, Berihun Mamo Negash
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Multilinear Regression Model to Estimate Mud Weight [PDF]
Nigerian Journal of Environmental Sciences and Technology, 2021 Estimation of mud weight poses a serious challenge to mud industries. In this study, a model was developed to tackle the problem of estimation of mud weight using multilinear regression techniques. The model was developed using data obtained from production records.
J. O. Oloro, T. E. Akhihiero
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Optimization of Dataset Generation for a Multilinear Regressive Road Traffic Noise Model [PDF]
WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT, 2023 According to the European Environmental Agency, road traffic noise is one of the worst and most prevalent kinds of environmental pollutants, which causes health problems to a constantly increasing number of people in urban areas throughout Europe. It has been proved that prolonged exposure to sound levels exceeding 55 dBA is harmful and causes severe ...
Rossi D., Mascolo A., Guarnaccia C.
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