multi-linear regression model
Simple and Multi Linear Regression Model of Verbs in Quran
... and multi-linear regression model of verbs in the Quran ...This model, gives an analysis for the influence to frequency of words with the form (—un, نو---) made by the frequency of ...
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ASSESSMENT OF LIQUEFACTION POTENTIAL OF SOIL USING MULTI-LINEAR REGRESSION MODELING
... Multi Linear Regression Model in terms of Cyclic Resistance Ratio (CRR) for soil profile was developed using SPSS (IBM SPSS Statistics ...CRR model for soil profile along its depth (z) ...
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Geometric Inference in Bayesian Hierarchical Models with Applications to Topic Modeling
... Bayesian multi-linear regression model, which aims to account for the multi-way interactions among predictor variables; part of our model construction includes a prior ...
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1. An empirical study on regression analysis to predict software effort based on use case points
... all regression models. Form the table 4 it can be observed that multi linear regression model has highest value of R 2 and ...best regression models, we consider one that should ...
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Automatic Modelling of Land Use Suitability Using Deep Feedforward Networks in Leon - Silao, Guanajuato Region
... a Linear Site Suitability Model based on The Multi-Level Logistic Regression (MLLR), implemented in Futures but used by other UGMs, with two nonlinear model variations based on a Deep ...
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The Impact of Economic Growth and Tax Reform on Tax Revenue and Structure: Evidence from China Experience
... statistics, multi-segment linear regression model and principal component analysis to analyze how economic growth and tax reform affect the total tax revenue and structure mainly from three ...
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Empirical Analysis of Exports, Imports and Industrial Value Added and Their Impact on Annual Growth Rate of Pakistan
... Exports of goods and services and industrial value added are considered the two pinnacle sectors in the economic growth of Pakistan. Today’s capital intensive international markets and Pakistan’s primary goods and labor ...
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Two-stage source tracking method using a multiple linear regression model in the expanded phase domain
... A LS TDE method based on the multiple linear regres- sion model via the interpolated phase expansion has been proposed. By the proposed phase expansion method, the IPD distribution between two channel sig- ...
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Quantitative structure activity relationship of matrix metalloproteinase inhibitors based on topological descriptors
... QSAR model: The top second QSAR model is obtained when multi linear regression analysis is done by taking connectivity index (order 1, standard) as first descriptor, valence ...
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Agricultural data prediction by means of neural network
... the multi-layer neural network for the prediction of the crop yield, and the comparison of the accu- racy of this approach with the accuracy of the well- known regression model designed for the ...
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... Forecasting model based on BP Neural Network for Crude Oil Production and Consumption in China was carried out by ...[10]. Multi linear regression has been used for oilfield output prediction ...
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Topological and Quantum chemical descriptors based Comparative Quantitative Structure Activity Relationship of benzothiazole derivatives
... QSAR model: The fifth QSAR model is obtained when multi linear regression analysis is done by taking heat of formation as first descriptor, total energy as second descriptor, HOMO ...
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INTEREST RATE DERIVATIVES IN THE SOUTH AFRICAN MARKET BASED ON THE PRIME RATE
... the multi-variable Engle-Granger methodology; it is essentially the same as above; the regression equation is simply a multi-linear equation, with dependent variable the prime rate and ...
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Predicting student performance in higher education using multi-regression models
... A multi-regression model with ten linear models gives and an RMSE of ...proposed model that practices the Lentera features have extra student Lentera collaboration information to study ...
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Estimation of water quality index using artificial intelligence approaches and multi-linear regression
... ANN model is presented in Table ...MLR model, the best model to estimate WQI was obtained to be ANN-II with the values of MSE, DC and RMSE are ...ANN model in a verification ...of ...
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Design optimization considering variable thermal mass, insulation, absorptance of solar radiation, and glazing ratio using a prediction model and genetic algorithm
... models, multi-linear regression (MLR) model and an artificial neural network (ANN) model, are developed to predict the building thermal performance and adopted as fitness functions for ...
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Plotting partial correlation and regression in ecological studies
... Multiple regression, the General linear model (GLM) and the Generalized linear model (GLZ) are widely used in ...fitted regression lines to document patterns in simple ...
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Obtaining an Accurate and Comprehensive Data Mining Model
... α and β are called the parameters of the true line. If these two parameters were known, the true line would be known, and the best possible prediction of what y can be made for any value of x. It is not expected that ...
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Pile design using Multiple Linear Regression model
... Multiple Linear Regression ” model, has been developed to produce a pile design ...MLR model developed for pre-stressed reinforced concrete pipe pile, cast in place reinforced concrete pile ...
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Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities
... probabilistic model for refining coarse-grained spatial data by utilizing auxiliary spatial data ...proposed model can effectively make use of auxiliary data sets with various granularities by ...
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