scholarly journals Overestimation of Radioactivity Concentration of Difficult-To-Measure Radionuclides in Scaling Factor Methodology

2021 ◽  
Vol 19 (3) ◽  
pp. 367-386
Author(s):  
Junghwan Park ◽  
◽  
Tae-Hyeong Kim ◽  
Jeongmook Lee ◽  
Junhyuck Kim ◽  
...  
Keyword(s):  
Scaling Factor ◽  
Radioactivity Concentration ◽  
Difficult To Measure Radionuclides ◽  
Scaling Factor Methodology

A Strong Tracking Cubature Kalman Filter for Nonlinear Estimation

2013 ◽  
Vol 313-314 ◽  
pp. 1115-1119
Author(s):  
Yong Qi Wang ◽  
Feng Yang ◽  
Yan Liang ◽  
Quan Pan
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Scaling Factor ◽  
Estimation Accuracy ◽  
Nonlinear State Estimation ◽  
Cubature Kalman Filter ◽  
Novel Method ◽  
Simulation Results ◽  
Tracking Filter ◽  
Nonlinear State

In this paper, a novel method based on cubature Kalman filter (CKF) and strong tracking filter (STF) has been proposed for nonlinear state estimation problem. The proposed method is named as strong tracking cubature Kalman filter (STCKF). In the STCKF, a scaling factor derived from STF is added and it can be tuned online to adjust the filtering gain accordingly. Simulation results indicate STCKF outperforms over EKF and CKF in state estimation accuracy.

Adaptive laguerre time scaling factor in predictive control

2003 ◽  
Vol 36 (16) ◽  
pp. 1339-1344
Author(s):  
M. El Adel ◽  
M. Ouladsine ◽  
J.C. Carmona
Keyword(s):  
Predictive Control ◽  
Scaling Factor ◽  
Time Scaling

A scaling factor theorem for homonuclear dipolar decoupling in solid-state NMR spectroscopy

2011 ◽  
Vol 212 (1) ◽  
pp. 11-16 ◽  
Author(s):  
Elodie Salager ◽  
Jean-Nicolas Dumez ◽  
Lyndon Emsley ◽  
Malcolm H. Levitt
Keyword(s):  
Solid State ◽  
Nmr Spectroscopy ◽  
Solid State Nmr ◽  
Scaling Factor ◽  
Solid State Nmr Spectroscopy ◽  
Factor Theorem

Logistic Map and Exponential Scaling Factor based Differential Evolution

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Differential Evolution ◽  
Logistic Map ◽  
Differential Evolution Algorithm ◽  
Scaling Factor ◽  
Exploration And Exploitation ◽  
Engineering Problems ◽  
Evolutionary Technique ◽  
Evolution Algorithm ◽  
State Of Art ◽  
Modified Algorithm

Differential evolution (DE), an important evolutionary technique, enhances its parameters such as, initialization of population, mutation, crossover etc. to resolve realistic optimization issues. This work represents a modified differential evolution algorithm by using the idea of exponential scale factor and logistic map in order to address the slow convergence rate, and to keep a very good equilibrium linking exploration and exploitation. Modification is done in two ways: (i) Initialization of population and (ii) Scaling factor.The proposed algorithm is validated with the aid of a 13 different benchmark functions taking from the literature, also the outcomes are compared along with 7 different popular state of art algorithms. Further, performance of the modified algorithm is simulated on 3 realistic engineering problems. Also compared with 8 recent optimizer techniques. Again from number of function evaluations it is clear that the proposed algorithm converses more quickly than the other existing algorithms.

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