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1. Full Text Least square support vector and multi‐linear regression for statistically downscaling general circulation model outputs to catchment streamflows
by Sachindra, D. A and Huang, F and Barton, A and Perera, B. J. C
International Journal of Climatology, ISSN 0899-8418, 04/2013, Volume 33, Issue 5, pp. 1087 - 1106
This study employed least square support vector machine regression (LS‐SVM‐R) and multi‐linear regression (MLR) for statistically downscaling monthly general... 
general circulation models | support vector machine | statistical downscaling | multi‐linear regression | streamflow | Multi-linear regression | Statistical downscaling | Support vector machine | General circulation models | Streamflow | AUSTRALIA | SCENARIOS | GCM SIMULATIONS | CLIMATE-CHANGE | RIVER-BASIN | PRECIPITATION | PREDICTORS | LOCAL CLIMATE | MACHINE | multi-linear regression | PROJECTIONS | METEOROLOGY & ATMOSPHERIC SCIENCES | Hydrology | Atmospheric research | Algorithms | Regression analysis | Analysis
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2. Full Text Simulation of groundwater level variations using wavelet combined with neural network, linear regression and support vector machine
by Ebrahimi, Hadi and Rajaee, Taher
Global and Planetary Change, ISSN 0921-8181, 01/2017, Volume 148, pp. 181 - 191
Simulation of groundwater level (GWL) fluctuations is an important task in management of groundwater resources. In this study, the effect of wavelet analysis... 
Wavelet | Support vector machine | Iran | Multi linear regression | Groundwater level | Time delay neural networks | GEOGRAPHY, PHYSICAL | GEOSCIENCES, MULTIDISCIPLINARY | MODEL | PREDICTION | Case studies | Water | Neural networks | Analysis | Water, Underground | Regression analysis | Management
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3. Comparison of regression and design models for biosorption process
by Çetintaş, Seda and Elevli, Sermin and Bingöl, Deniz
Desalination and Water Treatment, ISSN 1944-3994, 03/2019, Volume 145, pp. 107 - 119
In this study, the biosorption process were optimized and compared for the first time in terms of their accuracy and predictive ability for the sorption of... 
Biosorption | Full factorial design (FFD) | Multi linear regression (MLR) | Box-Behnken design (BBD) | Central composite design (CCD) | AQUEOUS-SOLUTIONS | HEAVY-METALS | CU(II) | RESPONSE-SURFACE METHODOLOGY | IONS | WATER RESOURCES | ADSORPTION | PREDICTION | ENGINEERING, CHEMICAL | CENTRAL COMPOSITE DESIGN | COPPER REMOVAL | OPTIMIZATION
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4. Automobile engine performance analysis using regression technique
by Sharma, Kartik and Sai Sabitha, A and Bansal, Abhay
Indian Journal of Science and Technology, ISSN 0974-6846, 2016, Volume 9, Issue 44
Prediction techniques | Automobiles | Data mining | Linear regression | Multi-Linear regression
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5. Full Text Multi-temporal Nonlinear Regression Method for Landsat Image Simulation
by Kim, Hye Jin and Kim, Hye Jin and Seo, Dae Kyo and Seo, Dae Kyo and Eo, Yang Dam and Eo, Yang Dam and Jeon, Min Cheol and Jeon, Min Cheol and Park, Wan Yong and Park, Wan Yong
KSCE Journal of Civil Engineering, ISSN 1226-7988, 2/2019, Volume 23, Issue 2, pp. 777 - 787
Optical remote sensing is limited in its potential for acquiring time-series images due to the restricted weather conditions in which it may be used. The... 
Engineering | multivariate adaptive regression splines | Civil Engineering | Gaussian process regression | Geotechnical Engineering & Applied Earth Sciences | multi linear regression | Industrial Pollution Prevention | MODIS products | Landsat image simulation | weather environmental parameters | ENGINEERING, CIVIL | SUPPORT VECTOR REGRESSION | MODIS | Temperature | Correlation | Parameters | Vegetative index | Methodology | Splines | Landsat | Radiation | Imaging techniques | Environmental factors | Regression analysis | Remote sensing | Image acquisition | Weather | Satellite imagery | Regressions | Spectroradiometers | Gaussian process | Simulation | Humidity | Process parameters | Visibility | Landsat satellites | 토목공학
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6. Full Text Predicting equilibrium vapour pressure isotope effects by using artificial neural networks or multi-linear regression – A quantitative structure property relationship approach
by Parinet, Julien and Julien, Maxime and Nun, Pierrick and Robins, Richard J and Remaud, Gerald and Höhener, Patrick
Chemosphere, ISSN 0045-6535, 09/2015, Volume 134, pp. 521 - 527
We aim at predicting the effect of structure and isotopic substitutions on the equilibrium vapour pressure isotope effect of various organic compounds... 
Multi-linear regression | Quantitative structure–property relationship | Equilibrium vapour pressure isotope effects | Artificial neural networks | Quantitative structure-property relationship | CARBON | FRACTIONATION | POLLUTANTS | QSPR MODEL | ADSORPTION | VOLATILIZATION | ENVIRONMENTAL SCIENCES | PETROLEUM-HYDROCARBONS | VAPORIZATION | Linear Models | Isotopes - analysis | Quantitative Structure-Activity Relationship | Vapor Pressure | Environmental Monitoring - methods | Neural Networks (Computer) | Neural networks | Analysis | Regression analysis | Vapour pressure | Isotope effect | Molecular structure | Vapor pressure | Regression | Mathematical models | Learning theory | Chemical Sciences
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7. Full Text Combined use of MILP and multi-linear regression to simplify LCA studies
by Pascual-González, Janire and Pozo, Carlos and Guillén-Gosálbez, Gonzalo and Jiménez-Esteller, Laureano
Computers and Chemical Engineering, ISSN 0098-1354, 11/2015, Volume 82, pp. 34 - 43
Life cycle assessment (LCA) has become the prevalent approach for quantifying the environmental impact of products over their entire life cycle. Unfortunately,... 
Streamlined LCA analysis | Multi-linear regression | Mixed-integer linear programming, Life cycle assessment | Environmental impact prediction | Life cycle assessment | ENGINEERING, CHEMICAL | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | ENERGY DEMAND | DATA GAPS | Mixed integer linear programming | Usage | Analysis | Regression analysis | Environmental auditing | Construction | Accuracy | Chemical engineering | Regression | Mathematical models | Indicators | Guidelines
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8. Age estimation system based on multivariate multi-linear regression
by Su, Ya
Journal of Advanced Oxidation Technologies, ISSN 1203-8407, 2018, Volume 21, Issue 2
Face images with aging variations display some sequential patterns that can be extracted by human. This is because age progression intrinsically has temporal... 
Under sample problem | Age estimation | Multi-variate multi-linear regression | CHEMISTRY, PHYSICAL | multi-variate multi-linear regression | under sample problem
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9. Full Text Evaluation of nitrate sources and the percent contribution of bacterial denitrification in hyporheic zone using isotope fractionation technique and multi-linear regression analysis
by Meghdadi, Aminreza and Javar, Narmin
Journal of Environmental Management, ISSN 0301-4797, 09/2018, Volume 222, pp. 54 - 65
Denitrification has documented as a promising pathway to permanently remove nitrate from a system. Numerous studies have used the isotope fractionation... 
Fecal bacterial group (Fecal coliform and Escherichia coli) | Nitrate isotopic enrichment | Ghezel-Ozan river | Isotope fractionation technique | Multi-linear regression analysis | Hyporheic denitrification | SOILS | COLONY-FORMING UNIT | RETENTION PROCESSES | FRESH-WATER | AMMONIUM | ENVIRONMENTAL SCIENCES | IN-SITU DENITRIFICATION | PROBABLE NUMBER | NITROGEN | CONSTRUCTED WETLAND | GROUNDWATER | Analysis | Constructed wetlands | Escherichia coli | Water, Underground | Denitrification | Regression analysis | Statistics | Methods | Aquifers
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10. Prediction models for CO2 emission in Malaysia using best subsets regression and multi-linear regression
by Tan, C.H and Matjafri, M.Z and Lim, H.S
Proceedings of SPIE - The International Society for Optical Engineering, ISSN 0277-786X, 2015, Volume 9638
multi linear regression | best subsets | Malaysia | trend analysis plots
Conference Proceeding
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11. Full Text Computational models for predicting anticancer drug efficacy: A multi linear regression analysis based on molecular, cellular and clinical data of oral squamous cell carcinoma cohort
by Robert, Beaulah Mary and Brindha, G.R and Santhi, B and Kanimozhi, G and Prasad, Nagarajan Rajendra
Computer Methods and Programs in Biomedicine, ISSN 0169-2607, 09/2019, Volume 178, pp. 105 - 112
The computational prediction of drug responses based on the analysis of multiple clinical features of the tumor will be a novel strategy for accomplishing the... 
Oral squamous cell carcinoma | Precision medicine | Multi linear regression | Computational models | Drug efficacy prediction | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | MEDICAL INFORMATICS | ENGINEERING, BIOMEDICAL | SENSITIVITY | COMPUTER SCIENCE, THEORY & METHODS | CANCER
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12. Full Text The QSPR models to predict the solubility of CO2 in ionic liquids based on least-squares support vector machines and genetic algorithm-multi linear regression
by Mehraein, Iliad and Riahi, Siavash
Journal of Molecular Liquids, ISSN 0167-7322, 01/2017, Volume 225, pp. 521 - 530
Global warming is an issue of high concern which is mostly caused by growing concentrations of carbon dioxide in the atmosphere. Many novel technologies offer... 
Support vector machines | Ionic liquids | Multi-linear regression | QSPR | Solubility | Carbon dioxide | CATALYSIS | GREEN SOLVENTS | MOLECULAR-STRUCTURE | CARBON-DIOXIDE ABSORPTION | SURFACTANTS | PHYSICS, ATOMIC, MOLECULAR & CHEMICAL | CHEMISTRY, PHYSICAL | PRESSURE PHASE-BEHAVIOR | AMINES | CAPTURE
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13. Full Text Study applicable for multi-linear regression analysis and logistic regression analysis
by Wu, Ju
Open Electrical and Electronic Engineering Journal, ISSN 1874-1290, 12/2014, Volume 8, Issue 1, pp. 782 - 786
Current study focus on using method of multi-linear regression analysis and logistic regression analysis, and discuss about the condition and scope of... 
Logistic regression analysis | Model-2 diabetes | Body mass index (BMI) | Glycosylated hemoglobin | Diabetes | Modeling method | Multi-linear regression analysis
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14. Full Text Support vector regression-based modeling of cumulative infiltration of sandy soil
by Sihag, Parveen and Tiwari, N.K and Ranjan, Subodh
ISH Journal of Hydraulic Engineering, ISSN 0971-5010, 02/2018, pp. 1 - 7
support vector regression | M5P tree model | multi-linear regression | generalized regression neural network | Cumulative infiltration
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15. Full Text Quantitative Structure-Retention Relationship study of the constituents of saffron aroma in SPME-GC–MS based on the Projection Pursuit Regression method
by Du, Hongying and Wang, Jie and Hu, Zhide and Yao, Xiaojun
Talanta, ISSN 0039-9140, 2008, Volume 77, Issue 1, pp. 360 - 365
Quantitative Structure-Retention Relationship (QSRR) studies were performed for predicting the retention times of 43 constituents of saffron aroma, which were... 
SPME-GC–MS | Projection Pursuit Regression (PPR) | Saffron | Quantitative Structure-Retention Relationship (QSRR) | Best Multi-Linear Regression (BMLR) | SPME-GC-MS | STORAGE | CHEMISTRY, ANALYTICAL | HEADSPACE | SOLID-PHASE MICROEXTRACTION | CHROMATOGRAPHY | PREDICTION | VOLATILES | INDEXES | Regression Analysis | Crocus - chemistry | Gas Chromatography-Mass Spectrometry - methods | Solid Phase Extraction - methods | Odorants - analysis | Quantitative Structure-Activity Relationship
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16. Multi linear regression model for mobile location estimation in GSM network
by Ezema, Longinus S and Ani, Cosmas I
Indian Journal of Science and Technology, ISSN 0974-6846, 2016, Volume 9, Issue 6
Received signal strength | Mobile location estimation | Multi-linear regression model | GPS | GSM network
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17. Full Text Forecasting long-term global solar radiation with an ANN algorithm coupled with satellite-derived (MODIS) land surface temperature (LST) for regional locations in Queensland
by Deo, Ravinesh C and Şahin, Mehmet
Renewable and Sustainable Energy Reviews, ISSN 1364-0321, 05/2017, Volume 72, pp. 828 - 848
Forecasting solar radiation ( ) is extremely crucial for engineering applications (e.g. design of solar furnaces and energy-efficient buildings, solar... 
Satellite-based solar model | Multi-linear regression | Neural network | ARIMA model | GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | LINEAR-REGRESSION MODELS | ENERGY & FUELS | ARTIFICIAL NEURAL-NETWORK | SUNSHINE DURATION | EXTREME LEARNING-MACHINE | GROUND MEASUREMENTS | HORIZONTAL SURFACE | EASTERN AUSTRALIA | DIFFUSE FRACTION | SUPPORT VECTOR MACHINE | CORAL-REEFS OPTIMIZATION | Architecture and energy conservation | Usage | Algorithms | Furnaces | Electric power-plants | Neural networks | Solar energy | Radiation | Environmental engineering | Power plants | Neurons
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18. Line Index of A-Type Stellar Astronomical Spectrum Predict Effective Temperature by Ridge Regression Model
by Xue, RZ and Chen, SX and Huang, HB
SPECTROSCOPY AND SPECTRAL ANALYSIS, ISSN 1000-0593, 08/2019, Volume 39, Issue 8, pp. 2624 - 2629
Line index is widely used in describing the features of spectral lines for astronomical objects because it retains the main physical characteristic information... 
Stellar spectra | Ridge regression | LAMOST (Large sky area multi-object fiber spectroscopy telescope) | SPECTROSCOPY | Lick line index | Linear model
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19. Full Text Intermittent reservoir daily-inflow prediction using lumped and distributed data multi-linear regression models
by MAGAR, R B and MAGAR, R B and JOTHIPRAKASH, V and JOTHIPRAKASH, V
Journal of Earth System Science, ISSN 0253-4126, 12/2011, Volume 120, Issue 6, pp. 1067 - 1084
In this study, multi-linear regression (MLR) approach is used to construct intermittent reservoir daily inflow forecasting system. To illustrate the... 
cause-effect models | time-series models | Earth Sciences | Extraterrestrial Physics, Space Sciences | combined models | lumped and distributed data | Multi-linear regression | Earth Sciences, general | Koyna reservoir inflow | ARIMA models | India | Combined models | Time-series models | Cause-effect models | Lumped and distributed data | RAINFALL-RUNOFF MODELS | RECONSTRUCTION | ARTIFICIAL NEURAL-NETWORK | RIVER | GEOSCIENCES, MULTIDISCIPLINARY | Reservoirs | Research | Hydraulic measurements | Regression analysis | Simulation | Weather forecasting | Watersheds | Meteorology
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20. Full Text Modeling of Health Related Quality of Life Using an Integrated Fuzzy Inference System and Linear Regression
by Abdullah, Lazim
Procedia Computer Science, ISSN 1877-0509, 2014, Volume 42, Issue C, pp. 99 - 105
Health Related Quality of Life (HRQL) is one of the increasing subjects used for assessing health condition among patients who suffer from specific diseases or... 
health status | chronic kidney diseases | Fuzzy inference system | inference rule | multi-linear regression | Multi-linear regression | Health status | Inference rule | Chronic kidney diseases
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