Approaches using the linear model
A Comparative View Of Applying Linear And Non-Linear Visualisation Approaches To Protein Dataset
... interpretability Linear model apply through drtoolbox where cyan circles represent HLA- A, red plus sign represents HLA-B and blue square represents ...in linear form then linear model ...
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3D Modelling With Linear Approaches Using Geometric Primitives
... study linear approaches for 3D model acquisition from non-calibrated ...3D model acquisition from a small number of arbitrary images with a reasonable amount of user ...
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Pile design using Multiple Linear Regression model
... One of the earliest applications of the SPT test is the determination of pile capacity. That includes two main approaches, direct and indirect methods (Nayak, 1985). Direct methods apply some modification factors ...
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The Effect of Creative Tasks on Electrocardiogram: Using Linear and Nonlinear Features in Combination with Classification Approaches
... B. Adaptive Neuro-Fuzzy Inference System The Adaptive Neuro-Fuzzy Inference System (ANFIS) classifier is used to obtain an improved diagnostic accuracy in the ECG signals (22) on creativity and normal states. The ...
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Estimation of water quality index using artificial intelligence approaches and multi-linear regression
... MLR model 3.2. Result of ANN model In ANN-feed forward was trained by the algorithm called ...ANN model is presented in Table ...MLR model, the best model to estimate WQI was obtained ...
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Comparative Analysis of Face Detection Using Linear Binary Techniques and Neural Network Approaches
... and model-based techniques [1] The reason for this short audit paper [2] is to introduce, order and assess some new face detection techniques utilizing four ordinary learning ...
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TRUCK ALLOCATION MODEL USING LINEAR PROGRAMMING AND QUEUEING THEORY
... allocation model in a mine can attain operational improvements by decreasing waiting times and achieve other benefits through enhanced optimal routing and grade ...allocation model in use, the complexity of ...
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Truck allocation model using linear programming and queueing theory
... allocation model in a mine can attain operational improvements by decreasing waiting times and achieve other benefits through enhanced optimal routing and grade ...allocation model in use, the complexity of ...
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Using linear mixed model and dummy variable model approaches to construct compatible single tree biomass equations at different scales – A case study for Masson pine in Southern China
... Possible limitation of the models The emphasis of this study is mainly on meth- odology. The applicability of the developed mod- els was influenced by the sample size and repre- sentation. As for the size of the sample, ...
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Hyperspectral unmixing with spectral variability using a perturbed linear mixing model
... new linear mixing model accounting for spatial and spectral endmember ...proposed model extended the classical LMM by including an additive spatially varying perturbation matrix that can capture end- ...
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New approaches in estimating linear regression model parameters in the presence of multicollinearity and outliers
... menganggarkan model regresi dengan multikolinearan dan yang mempunyai ciri-ciri titik ...berdasarkan model terbaik dengan kecenderungan dan ralat punca kuasa dua min bagi data simulasi dan ralat piawai yang ...
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Modeling of ambulatory heart rate using linear and neural network approaches
... The neo-fuzzy neuron (NFN) was proposed as a s imp le neuro-fuzzy arch i tec ture w i th very fas t learn ing and guaran tee for the convergence to the g loba l m in imum of the err[r] ...
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Prediction Model of Air Pollutant Levels Using Linear Model with Component Analysis
... Using 30-mins interval concentrations of NO 2 , PM 10 , and O 3 , we have indicated the effect of other pollutants effect and meteorological factors. The ultimate benefit on using such short interval data ...
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Fuzzy Approaches for Multiobjective Fuzzy Random Linear Programming Problems Through a Probability Maximization Model
... fuzzy approaches are proposed for not only multiobjective stochastic linear program- ming problems, but also multiobjective fuzzy random linear programming problems through a probability maximization ...
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The Heteroskedasticity Test Implementation for Linear Regression Model Using MATLAB
... regression model, homoskedasticity, testing for heteroskedasticity, software environment MATLAB Received: September 23, 2017 The article discusses the problem of heteroskedasticity, which can arise in the process ...
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Prediction of gestational age by ultrasonogram using linear regression model
... Director, Research Centre for Cellular Genomics, Sree Balaji Medical College and Hospital and Hospital Estimation of an accurate due date is of both social and medical significance. Care providers are dependent on ...
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Using generalized linear models to model compositional response data
... the model parameters, which makes this system of estimating the parameters very ...with using such a system, however, is that the sum of the estimated means is not constrained to be equal to ...
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Prediction of Heart Disease using Multiple Linear Regression Model
... IJEDR1704226 International Journal of Engineering Development and Research (www.ijedr.org) 1424 Figure 4: Predicting Multiple Linear Regression Algorithm V. CONCLUSION Today diagnosing patients correctly and ...
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Growth Analysis in Rabbit Using Gompertz Non-linear Model
... Individual body weights of each breed was measured from birth to 63 days of age with 3-days interval. Those periodical data were separated into different sex, be then it was averaged to analysis growth pattern. Growth ...
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Prototype development model for conveyor using linear induction motor
... To study design and winding technique of linear induction motor. The purpose of this project is to increase use of LIM in industry for transportation purpose. The low rating LIM are of low cost, low energy ...
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