Home  About us  Contact
 

Marquardt Algorithm (marquardt + algorithm)

Distribution by Scientific Domains
Engineering40%
Chemistry40%

Selected Abstracts

A study on non-invasive detection of blood glucose concentration from human palm perspiration by using artificial neural networks

EXPERT SYSTEMS, Issue 3 2010
Hamdi Melih Sarao
Abstract: In this paper the relationship between blood glucose concentration and palm perspiration rate is studied as a non-invasive method. A glucose concentration range from 83 mg/dl to 116.5 mg/dl is examined. An artificial neural network (ANN) trained by the Levenberg,Marquardt algorithm is developed to detect the performance indices based on the one- and two-input variables. A data set for 72 volunteers is used for this study. Data of 36 volunteers are used for training the ANN and data of 36 volunteers were reserved for testing. Results of the study are acceptable with an error of 8.38% for the Elman neural network and 8.77% for the multilayer neural network. Therefore, the palm perspiration rate may be used as a good indicator for detecting glucose concentration in blood. This non-invasive method has advantages such as time saving, cost etc. over other methods and it is painless. The results of clinical experiments, follow-up methods and other applications are presented. [source]

Parameter identification for lined tunnels in a viscoplastic medium

INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS, Issue 12 2002
B. Lecampion
Abstract This paper is dedicated to the identification of constitutive parameters of elasto-viscoplastic constitutive law from measurements performed on deep underground cavities (typically tunnels). This inverse problem is solved by the minimization of a cost functional of least-squares type. The exact gradient is computed by the direct differentiation method and the descent is done using the Levenberg,Marquardt algorithm. The method is presented for lined or unlined structures and is applied for an elastoviscoplastic constitutive law of the Perzyna class. Several identification problems are presented in one and two dimensions for different tunnel geometries. The used measurements have been obtained by a preliminary numerical simulation and perturbed with a white noise. The identified responses match the measurements. We also discuss the usage of the sensitivity analysis of the system, provided by the direct differentiation method, for the optimization of in situ monitoring. The sensitivity distribution in space and time assess the location of the measurements points as well as the time of observation needed for reliable identification. Copyright © 2002 John Wiley & Sons, Ltd. [source]

Prediction model for increasing propylene from FCC gasoline secondary reactions based on Levenberg,Marquardt algorithm coupled with support vector machines

JOURNAL OF CHEMOMETRICS, Issue 9 2010
Xiaowei Zhou
Abstract Levenberg,Marquardt (LM) algorithm was adopted to optimize the multiple parameters of the support vector machines (SVM) model to overcome the difficulty in selecting the parameters of SVM and to fit relational expression of high nonlinearity. Strategy of dividing the training data into working data to train SVM and the testing data so as to avoid over-fitting was performed. Comparison of the proposed LM/SVM method with three reported hybridized SVM approaches (GA/SVM, SM/SVM and SQP/SVM) was also carried out. The new method was applied in modelling for the prediction of propylene by secondary reactions of FCC gasoline. Best performance of LM/SVM employing polynomial kernel was demonstrated. Good agreement between predicted results and experimental data suggests that the LM/SVM method is successfully developed and the SVM model for increasing propylene is well established. Finally, sequential quadratic programming (SQP) algorithm was employed to optimize the operation conditions of FCC gasoline secondary reaction for maximizing the propylene yield. The obtained optimization conditions are consistent with experimental data and reported results, indicating that the optimization results are reliable. Copyright © 2010 John Wiley & Sons, Ltd. [source]

INFLUENCE OF SAMPLE SIZE AND SHAPE ON TRANSPORT PARAMETERS DURING DRYING OF SHRINKING BODIES

JOURNAL OF FOOD PROCESS ENGINEERING, Issue 2 2007
NAJMUR RAHMAN
ABSTRACT An experimental investigation on the influence of sample size and shape on heat and mass transport parameters under natural convection air-drying is presented. Potato cylinders with length of 0.05 m and thicknesses of 0.005, 0.008, 0.010 and 0.016 m, and circular slices with diameter of 0.05 m and thickness of 0.01 m were dried in a laboratory scale hot-air cabinet dryer. Results indicate that each transport parameter exhibits a linear relationship with sample thickness. Convective heat and mass transfer coefficients (hcand hm) decreased whereas moisture diffusion coefficient (Deff) increased with increasing thickness. Considering no sample shrinkage effect in the parameter analysis, for the thickness range considered, the values of hcare found to be underestimated in the range of 29.0,30.6%, whereas those of hmand Deff are overestimated in the range of 33.7,38.0% and 75.9,128.1%, respectively. Using Levenberg,Marquardt algorithm for optimization, a correlation for Biot number for mass transfer (Bim) as a function of drying time and sample thickness is proposed. A close agreement was observed between dimensionless moisture contents predicted by this relation and those obtained from experiments for different sample thicknesses at drying air temperature of 60C. For the same thickness and drying conditions, circular slices caused an increase in each transport parameter significantly. [source]

Properties of analytic transit light-curve models

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 1 2008
András Pál
ABSTRACT In this paper, a set of analytic formulae is presented with which the partial derivatives of the flux obscuration function can be evaluated , for planetary transits and eclipsing binaries , under the assumption of quadratic limb darkening. The knowledge of these partial derivatives is crucial for many of the data modelling algorithms and estimates of the light-curve variations directly from the changes in the orbital elements. These derivatives can also be utilized to speed up some of the fitting methods. A gain of ,8 in computing time can be achieved in the implementation of the Levenberg,Marquardt algorithm, relative to using numerical derivatives. [source]