Estimation of real parameter

2019 ◽  
pp. 43-92
Author(s):  
Jana Jurečková ◽  
Jan Picek ◽  
Martin Schindler
Keyword(s):  
Real Parameter

Real-Parameter Constrained Optimization using Enhanced Quality-Based Cultural Algorithm with Novel Influence and Selection Schemes

2021 ◽  
Author(s):  
Rami S. Al-Gharaibeh ◽  
Mostafa Z. Ali ◽  
Mohammad I. Daoud ◽  
Rami Alazrai ◽  
Heba Abdel-Nabi ◽  
...  
Keyword(s):  
Constrained Optimization ◽  
Real Parameter ◽  
Cultural Algorithm

Real-parameter evolutionary multimodal optimization — A survey of the state-of-the-art

2011 ◽  
Vol 1 (2) ◽  
pp. 71-88 ◽  
Author(s):  
Swagatam Das ◽  
Sayan Maity ◽  
Bo-Yang Qu ◽  
P.N. Suganthan
Keyword(s):  
State Of The Art ◽  
The State ◽  
Real Parameter ◽  
Multimodal Optimization

Real-parameter crossover operators with multiple descendents: An experimental study

2008 ◽  
Vol 23 (2) ◽  
pp. 246-268 ◽  
Author(s):  
A. M. Sánchez ◽  
M. Lozano ◽  
C. García-Martínez ◽  
D. Molina ◽  
F. Herrera
Keyword(s):  
Experimental Study ◽  
Real Parameter

Generalising a triangle inequality

2018 ◽  
Vol 102 (555) ◽  
pp. 422-427
Author(s):  
Zoltan Retkes
Keyword(s):  
Original Problem ◽  
Triangle Inequality ◽  
Real Parameter ◽  
Geometrical Inequality

The main goal of this paper is to give a deeper understanding of the geometrical inequality proposed by Martin Lukarevski in [1]. In order to formulate our results we shall introduce and use the following notation throughout this paper. Let A1A2A3 be a triangle a1, a2, a3, the lengths of the sides opposite to A1, A2, A3 respectively, P an arbitrary inner point of it xi, the distance of P from the side of length ai. Let r, R be the inradius and circumradius of the triangle hi, the altitude belonging to side ai, Δ the area and finally let α be a real parameter. We adopt also the use of Σui to refer the sum taken over the suffices i = 1, 2, 3. Now we are in the position to reformulate the original problem into a more general form namely: find bounds for Σxαi in terms of r and R. The main results of our investigation are summarised in the following theorem.

Experimental Estimation of Shear Wave Velocity Profile Using MASW Method and Inversion Technique

2013 ◽  
Vol 300-301 ◽  
pp. 955-958
Author(s):  
Pei Hsun Tsai ◽  
Chih Chun Lou
Keyword(s):  
Genetic Algorithm ◽  
Velocity Profile ◽  
Dispersion Curve ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Dispersion Curves ◽  
Real Parameter ◽  
Shear Wave Velocity Profile ◽  
Experimental Dispersion

In the paper the shear wave velocity profile is studied using the MASW test. The experimental dispersion curves were obtained from the signal process proposed by Ryden. Theoretical dispersion curve can be constructed by thin layer stiffness matrix method. A real-parameter genetic algorithm is required to minimize the error between the theoretical and experimental dispersion curves. To reduce the error of experimental and theoretical dispersion curve using real-parameter genetic algorithm is feasible. The results show that the soil layers of the study area can be modeled as a sandy fill overlaid on an underlying half space. Test results also show that the asymptotes at high frequencies of the fundamental mode approach the phase velocities for the fill of 190 m/s. The depths of weathered bedrock estimating from dispersion curves match well with that of borehole data.

Sign in / Sign up

Export Citation Format

Share Document