نتایج جستجو برای: Multiple linear regressions (MLR)
تعداد نتایج: 1203338 فیلتر نتایج به سال:
In this paper, the quantitative structure activity-relationship (QSAR) of the CCR2b receptor inhibitors was scrutinized. Firstly, the molecular descriptors were calculated using the Dragon package. Then, the stepwise multiple linear regressions (SW-MLR) and the genetic algorithm multiple linear regressions (GA-MLR) variable selection methods were subsequently employed to select and implement th...
in this paper, the quantitative structure activity-relationship (qsar) of the ccr2b receptor inhibitors was scrutinized. firstly, the molecular descriptors were calculated using the dragon package. then, the stepwise multiple linear regressions (sw-mlr) and the genetic algorithm multiple linear regressions (ga-mlr) variable selection methods were subsequently employed to select and implement th...
Quantitative structure-activity relationship (QSAR) models were employed for prediction the activity of P2X7 receptor antagonists. A data set consisted of 50 purine derivatives was utilized in the model construction where 40 and 10 of these compounds were in the training and test sets respectively. A suitable group of calculated molecular descriptors was selected by employing stepwise multiple ...
quantitative structure-activity relationship (qsar) models were employed for prediction the activity of p2x7 receptor antagonists. a data set consisted of 50 purine derivatives was utilized in the model construction where 40 and 10 of these compounds were in the training and test sets respectively. a suitable group of calculated molecular descriptors was selected by employing stepwise multiple ...
qspr study on benzene derivatives have been made using recently introduced topological methodology. in this study the relationship between the randic' (x'), balaban (j), szeged (sz),harary (h), wiener (w), hyperwiener and wiener polarity (wp) to the thermal energy (eth), heat capacity (cv) and entropy (s) of benzene derivatives is represented.physicochemical properties are taken from the quantu...
The main objective of the research is to compare the accurateness of Artificial Neural Networks (ANN) and Multiple Linear Regressions (MLR) model for Specific Fuel Consumption for pyrolysis oil blended with diesel used in a single cylinder diesel engine. In this study, parameters i. e. Injection Timing, Injection Pressure, Compression Ratio, and Load are taken. Artificial Neural Networks (ANN) ...
quantitative relationships between molecular structure and azolo-adamantanes derivatives were discovered by different chemometric tools including factor analysis based multiple linear regressions (fa-mlr), principle component regression analysis (pcra), and genetic algorithm-partial least squares ga-pls. the fa-mlr describes the effect of geometrical and quantum indices on enzyme inhibition act...
Revealing the failure of agile software projects is a great challenge faced by companies. This paper focuses on using intelligent techniques such as fuzzy logic, multiple linear regressions, support vector machine, neural network to address this challenge. also presents review some works related area interest. In paper, researchers propose an approach for revealing based two techniques: logic a...
in this work quantitative structure activity relationship (qsar) methodology was applied for modeling and prediction of cellular response to polymers that have been designed for tissue engineering. after calculation and screening of molecular descriptors, linear and nonlinear models were developed by using multiple linear regressions (mlr) and artificial neural network (ann) methods. the root m...
In this work quantitative structure activity relationship (QSAR) methodology was applied for modeling and prediction of cellular response to polymers that have been designed for tissue engineering. After calculation and screening of molecular descriptors, linear and nonlinear models were developed by using multiple linear regressions (MLR) and artificial neural network (ANN) methods. The root m...
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