Results 171 to 180 of about 12,139 (206)
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Journal of Electronics,Computer Networking and Applied Mathematics, 2023
In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions.
Thaer, Hashim, Abdulmuttaleb
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In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions.
Thaer, Hashim, Abdulmuttaleb
openaire +2 more sources
Journal of Hydrologic Engineering - ASCE, 2013
Precipitation is the primary driver for hydrologic modeling. Because hydrologic models often require long-term, spatially dis- tributed precipitation data sets for calibration and validation, a novel approach was developed to generate spatially distributed precipitation data using an artificial neural network (ANN) for the periods when Next-Generation ...
Suresh Sharma +2 more
exaly +2 more sources
Precipitation is the primary driver for hydrologic modeling. Because hydrologic models often require long-term, spatially dis- tributed precipitation data sets for calibration and validation, a novel approach was developed to generate spatially distributed precipitation data using an artificial neural network (ANN) for the periods when Next-Generation ...
Suresh Sharma +2 more
exaly +2 more sources
Computers in Biology and Medicine, 2008
In this study, the performances of artificial neural network (ANN) analysis and multilinear regression (MLR) model-based estimation of heart rate were compared in an evaluation of individual cognitive workload. The data comprised electrocardiography (ECG) measurements and an evaluation of cognitive load that induces psychophysiological stress (PPS ...
Kerttu Huttunen, Tomi Laitinen
exaly +3 more sources
In this study, the performances of artificial neural network (ANN) analysis and multilinear regression (MLR) model-based estimation of heart rate were compared in an evaluation of individual cognitive workload. The data comprised electrocardiography (ECG) measurements and an evaluation of cognitive load that induces psychophysiological stress (PPS ...
Kerttu Huttunen, Tomi Laitinen
exaly +3 more sources
iPhone Sales Prediction Based on Multilinear Regression Model: Evidence from Statista
2023 IEEE International Conference on Sensors, Electronics and Computer Engineering (ICSECE), 2023exaly +2 more sources
MIA-QSAR modelling of activities of a series of AZT analogues: bi- and multilinear PLS regression
Molecular Simulation, 2010The activities of a series of azidothymidine derivatives, compounds with anti-HIV potency, were computationally modelled using multivariate image analysis applied to quantitative structure–activity relationships (MIA-QSAR). Two regression methods were tested in order to find the best correlation between actual and predicted activities: bilinear ...
Goodarzi, Mohammad +1 more
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2020
Education system is the most important aspect of any society as it directly affects employability. In today’s modern era the number of graduates is on rise but when we look at the rate of employability of these graduates it is very poor. In this paper, we try to understand IT graduate attributes by working on the database collected from aspiring minds (
Ankita Chopra, Madan Lal Saini
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Education system is the most important aspect of any society as it directly affects employability. In today’s modern era the number of graduates is on rise but when we look at the rate of employability of these graduates it is very poor. In this paper, we try to understand IT graduate attributes by working on the database collected from aspiring minds (
Ankita Chopra, Madan Lal Saini
openaire +1 more source
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 ...
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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 ...
openaire +2 more sources
Journal of the Energy Institute, 2020
Abstract This study shows a mathematical and statistical analysis to generate models based on multiple linear regression (MLR) and regression trees (RT) that allow a reliable prediction of the Mass Yield (MY) and the Higher Heating Value (HHV) of the final solid product obtained by Hydrothermal Carbonization, called hydrochar.
Fidel Vallejo +3 more
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Abstract This study shows a mathematical and statistical analysis to generate models based on multiple linear regression (MLR) and regression trees (RT) that allow a reliable prediction of the Mass Yield (MY) and the Higher Heating Value (HHV) of the final solid product obtained by Hydrothermal Carbonization, called hydrochar.
Fidel Vallejo +3 more
openaire +1 more source
Journal of Chemical Information and Modeling, 2007
During the last years, considerable effort has been devoted to model the toxicity of chemicals to Tetrahymena pyriformis for medium and large sized data sets using various artificial neural network (ANN) techniques. Motivation behind this has been to model highly complex relationships with nonlinear character making it possible to describe wide ...
Iiris Kahn, Sulev Sild, Uko Maran
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During the last years, considerable effort has been devoted to model the toxicity of chemicals to Tetrahymena pyriformis for medium and large sized data sets using various artificial neural network (ANN) techniques. Motivation behind this has been to model highly complex relationships with nonlinear character making it possible to describe wide ...
Iiris Kahn, Sulev Sild, Uko Maran
openaire +2 more sources
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023
Ben Gabrielson +4 more
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Ben Gabrielson +4 more
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