JPEG based steganography methods using Cohort Intelligence with Cognitive Computing and modified Multi Random Start Local Search optimization algorithms

2018 ◽  
Vol 430-431 ◽  
pp. 378-396 ◽  
Author(s):  
Dipti Kapoor Sarmah ◽  
Anand J. Kulkarni
2019 ◽  
Vol 7 (4) ◽  
pp. 321-328
Author(s):  
Nelson Ricardo Flores Zuniga

In the last decade, many works compared nonhyperbolic multiparametric travel-time approximations to perform velocity analysis. In these works, some analyses were accomplished, such as accuracy analysis and objective function analysis. However, no previous works compared the optimization algorithms to perform the inversion procedure concerning the processing time and the accuracy of each algorithm. As the shifted hyperbola showed the best results among the unimodal approximations in previous works, it was selected to be used in a comparison with five local search optimization algorithms. Each algorithm was compared concerning the accuracy by the minimization of the calculated curve to the observed curve. The travel-time curves tested here are conventional (PP) and converted wave (PS) reflection events from an offshore model. With this set of tests, it is possible to define which optimization algorithm presents the most reliable result when used with the shifted hyperbola equation concerning the processing time and the accuracy.


Author(s):  
Renaud De Landtsheer ◽  
Fabian Germeau ◽  
Thomas Fayolle ◽  
Gustavo Ospina ◽  
Christophe Ponsard

Author(s):  
Mohamed B. Trabia ◽  
Xiao Bin Lu

Abstract Optimization algorithms usually use fixed parameters that are empirically chosen to reach the minimum for various objective functions. This paper shows how to incorporate fuzzy logic in optimization algorithms to make the search adaptive to various objective functions. This idea is applied to produce a new algorithm for minimization of a function of n variables using an adaptive form of the simplex method. The search starts by generating a simplex with n+1 vertices. The algorithm replaces the point with the highest function value by a new point. This process comprises reflecting the point with the highest function value in addition to expanding or contracting the simplex using fuzzy logic controllers whose inputs incorporate the relative weights of the function values at the simplex points. The efficiency of the algorithm is studied using a set of standard minimization test problems. This algorithm generally results in a faster convergence toward the minimum. The algorithm is also applied successfully to two engineering design problems.


2018 ◽  
Vol 210 ◽  
pp. 04052 ◽  
Author(s):  
Nadia Abd-Alsabour

Local search algorithms perform an important role when being employed with optimization algorithms tackling numerous optimization problems since they lead to getting better solutions. However, this is not practical in many applications as they do not contribute to the search process. This was not much studied previously for traditional optimization algorithms or for parallel optimization algorithms. This paper investigates this issue for parallel optimization algorithms when tackling high dimensional subset problems. The acquired results show impressive recommendations.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 145469-145488
Author(s):  
Habeeb Bello-Salau ◽  
Adeiza James Onumanyi ◽  
Adnan M. Abu-Mahfouz ◽  
Achonu O. Adejo ◽  
Muhammed Bashir Mu'Azu

2016 ◽  
Vol 82 ◽  
pp. 01017
Author(s):  
Ming-Ang Yin ◽  
Zhi-Li Sun ◽  
Jian Wang ◽  
Yu Guo

Sign in / Sign up

Export Citation Format

Share Document