Results 181 to 190 of about 12,024 (199)

Modeling the Toxicity of Chemicals toTetrahymenapyriformisUsing Heuristic Multilinear Regression and Heuristic Back-Propagation Neural Networks

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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Two-dimensional Monte Carlo simulation coupled with multilinear regression modeling of source-specific health risks from groundwater

Journal of Hazardous Materials
Effective protection of groundwater requires an accurate health risk assessment of contaminants; however, the diversity of pollution sources, variability, and uncertainties in exposure parameters present significant challenges in this assessment. In this study, groundwater risk estimates associated with NO3-, and F-, along with fourteen heavy metal ...
Jelena Vesković, Antonije Onjia
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ChemInform Abstract: Modeling the Toxicity of Chemicals to Tetrahymena pyriformis Using Heuristic Multilinear Regression and Heuristic Back‐Propagation Neural Networks.

ChemInform, 2008
AbstractChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
Iiris Kahn, Sulev Sild, Uko Maran
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Evaluating Degree‐Based Topological Indices in QSPR Modeling of Anticancer Drugs Using Linear and Multilinear Regression

International Journal of Quantum Chemistry
ABSTRACT Cancer arises from the rapid growth of aberrant cells within the body. A range of treatment options are available, including surgery, radiation, hormone therapy, and more, for managing this perilous condition.
Bharathi Shettahalli Nagaraje Urs, S. Krishnamurthy, K. Anand Solomon, Deepika Togarichetu   +3 more
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Developing Alternative Multilinear Regression-Based Intelligence Hybrid Model

Kehinde Adewale Adesina, Mohammad Yazdi
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Development of Multilinear Regression Models for Online Voltage Stability Margin Estimation

IEEE Transactions on Power Systems, 2011
This paper investigates the use of reactive power reserves (RPR) as an indicator to estimate voltage stability margin (VSM) in an online environment. The methodology relies upon the relationship between system-wide RPRs and VSM. Statistical multilinear regression models (MLRM) are utilized in order to express how variations in RPRs can be transformed ...
Bruno Leonardi, Venkataramana Ajjarapu
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Sensitivity Analysis of the Calibration of Dataset for a Road Traffic Noise Multilinear Regressive Model

2023 27th International Conference on Circuits, Systems, Communications and Computers (CSCC), 2023
Quantitative evaluation of noise levels is of great importance for the overall evaluation of inhabited contexts. Road traffic noise is a pervasive kind of pollution, which causes health problems to people exposed to sound levels exceeding 55 dBA.
Domenico Rossi, Aurora Mascolo, Claudio Guarnaccia   +2 more
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Unveiling the adsorption mechanisms of macrolides by mesoporous carbons through molecular dynamics simulation and multilinear regression modelling

Separation and Purification Technology
Hongjun Zhao, Xinzong Xiao, Yitao Lyu, Jingrun Hu, Yi Jiang, Min Li, Weiling Sun   +6 more
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Comparison between artificial neural network and multilinear regression models in an evaluation of cognitive workload in a flight simulator

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 ...
Manne, Hannula, Kerttu, Huttunen, Jukka, Koskelo, Tomi, Laitinen, Tuomo, Leino   +4 more
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Prediction of Single‐Pool Kt/V Based on Clinical and Hemodialysis Variables Using Multilinear Regression, Tree‐Based Modeling, and Artificial Neural Networks

Artificial Organs, 2003
Abstract: The impact of clinical and other variables on single‐pool Kt/V (spKt/V) is unclear. The goal of this study was to identify clinical and hemodialysis treatment related predictors of spKt/V and use multilinear regression (LM), tree‐based modeling (TBM), and artificial neural networks (ANN) to predict actual spKt/V. When 602 hemodialysis records
Alexander, Goldfarb-Rumyantzev, Michael H, Schwenk, Samuel, Liu, Chaim, Charytan, Bruce S, Spinowitz   +4 more
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