Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 63 for “"non-linear regression"”.
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Use of the Gompertz equation to model non-linear survival curves and predict temperature, pH, and sodium chloride effects for Listeria monocytogenes Scott A
Numerous examples of non-linear survival curves, plotted as log surviving cells vs. time, for bacteria exposed to heat have been reported. Factors which may affect the shape of a survival curve and the heat resistance of bacteria include temperature, pH, and NaCl concentration. Many studies have …
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Nesting Biology of Osmia cornifrons: Implications for Population Management
… and of C. krombeini was determined using linear and non-linear regression analysis. Results indicated that C. krombeini is more frequently found in the cells of female O. cornifrons and that female O. cornifrons suffer greater mortality than male O. cornifrons due to C. krombeini. Second, …
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Physics-Based Artificial Intelligence Models for Vehicle Emissions Prediction
… compression ignition engines primarily depend non-linearly on three parameters: adiabatic flame temperature, intake oxygen concentration, and combustion time duration. Here, these parameters were calculated from available OBD data. Non-linear regression coupled with a novel Divergent Window …
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An explorative study of linear vs non-linear hedonic pricing of second-hand cars in South Africa
… Using a hedonic pricing approach to develop four linear and four non-linear regression models the study analyses a comprehensive dataset of 4,386 second-hand vehicles collected from the Cars.co.za website in 2018 and focuses on eight key vehicle attributes, namely age, mileage, region (province of …
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Bayesian approach to inference and variable selection for misclassified and under-reported response models.
… a subset of significant covariates in non-linear regression. In particular, we consider non-differential misclassification in logistic regression and non-differential under-reporting in Poisson regression. Differential misclassification and differential under-reporting are also …
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A system for the acquisition and digital analysis of lower limb flow waveforms
… of the lower limb arterial circulation using a non-linear regression technique of curve fitting in the time domain. A pilot study using the system shows a significant separation (p < 0.001 Mann Whitney U-test) between the damping factors of a normal control group (quartile range = 0. 15 - 0.25 ; …
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Analysis of a high resolution deep ocean acoustic navigation system
… times between survey points and transponders. Non-linear regression techniques are employed to develop a maximum likelihood estimator for net element positions based on these phase and travel time measurements. An approximate error covariance matrix is generated and an optimum choice of survey …
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Compatible taper and volume equations for yellow-poplar in West Virginia
… the mathematical integration of taper functions. Non-linear regression techniques were employed to estimate the parameters in both the taper and volume functions while accounting for correlated error structures. This technique was used to simultaneously minimize the error in both the taper and …
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View-dependent precomputed light transport using non-linear Gaussian function approximations
… operator based on sums of Gaussians. The non-linear parameters of the representation allow for 1) arbitrary bandwidth because scale is encoded as a direct parameter; and 2) high-quality interpolation across view and mesh triangles because we interpolate the average direction of the …
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A generalised feedforward neural network architecture and its applications to classification and regression
… that allows them to operate as adaptive non-linear filters. Shunting Inhibitory Artificial Neural Networks (SIANNs) are biologically inspired networks where the basic synaptic computations are based on shunting inhibition. SIANNs were designed to solve difficult machine learning problems …
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A transient heat probe sensor for measuring transpiration in the stem of woody plants.
… can not be analysed as a first order model. Non-linear regression analysis showed that the relationship between the probe sensor temperature response and the time elapsed from the beginning of cooling phase is adequately fitted by an additive exponential model. A dimensionless heat transfer …
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Quantification of uncertainty of geometallurgical variables for mine planning optimisation
… a geometallurgical block model. Bootstrapped non-linear regression models by projection pursuit were built to predict grindability indices and recovery, and quantify model uncertainty. These models are useful for populating the geometallurgical block model with response attributes. New …
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An investigation of resistance spot welding current and time parameters for different thicknesses of SAE CR 1010 steel
… thicknesses under investigation, based on non-linear regression techniques. From the prediction models and the use of Calculus, the maximum tensile-shear strengths and corresponding maximum weld cycles were computed. The minimum weld strengths and weld cycles were determined by the welding …
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Strategic behavior in risky competitive settings
… the Lagrange Multiplier test in several popular linear and non-linear regression models: the multivariate linear probability model, the conditional and unconditional multinomial model, the multinomial logit and probit models; as well as the overidentifying restrictions test in GMM. Therefore, …
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Dealing with measurement error in covariates with special reference to logistic regression model: a flexible parametric approach
… response or outcome variable through a suitable regression model. The accuracy of such quantification depends on how precisely we measure the relevant covariates. In many instances, we can not measure some of the covariates accurately, rather we can measure noisy versions of them. In statistical …
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Biojutiklių atsako kreivių ir medžiagų koncentracijų regresinė analizė /
The purpose of this work is to create non liner regression model with optimal number of coefficients and optimal values of these coefficients, and predict liquor concentration having values of amperimetric data. The main task of the work: • To use Semi-supervised learning algorithm while creating …
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Limitations of Initial Orbit Determination Methods for Low Earth Orbit CubeSats with Short Arc Orbital Passes
… predict a secondary observation session. Finally non-linear regression will be performed to determine if the error metrics follow a predictable trend based on how much orbital arc is seen by the observer. It was determined that above a certain amount of orbital arc, angles only IOD methods can …
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Investigating the frequency behavior of fluidic oscillators and their application as active flow control for an SNLF airfoil
… different inlet conditions. A multi-variate non-linear regression procedure was used to build a model to predict the frequency behavior of a fluidic oscillator given a set of internal geometries and inlet conditions. The SNLF S414 airfoil is a multi-element airfoil with an open slot to …
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Sonoelastography of the Supraspinatus Tendon: Correlation Analysis with T2* Mapping of the Supraspinatus Tendon on 3 Tesla MRI
… and standard deviation (T2*h) of T2* values. Linear and non-linear regression analyses were performed to find the best functions to fit each parameter. Results: The mean strain ratio S/D was 0.65 ± 0.33 on sonoelastography. T2*bulk and T2*h in the supraspinatus tendons were 21.8 ± 5.4 and 6.3 …
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