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Gravity inversion of basement relief using imperialist competitive algorithm with hybrid techniques

Joolaei Amir, Arab Amiri-Alireza, Nejati Ali

Acta Geophysica

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2022

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Vol. 70, no 6

2629--2646

EN

Classically, local deterministic optimization techniques have been employed to solve such nonlinear gravity inversion problem. Nevertheless, local search methods can also be easily implemented and demonstrate higher rates of convergence; but in highly nonlinear cases such as geophysical problems, they require a reliable initial model which should be adequately close to the true model. Recently, global optimization methods have shown promising results as an alternative to classical inversion methods. Each of the global optimization algorithms has unique benefits and faults; therefore, applying different combinations of them is one of the proposed solutions for overcoming their distinct limitations. In this research, the design and implementation of the hybrid method based on a combination of the imperialist competitive algorithm (ICA) and firefly algorithm (FA) as tools of two-dimensional nonlinear modeling of gravity data and as a substitute for the local optimization methods were investigated. Hybrid of ICA and FA algorithm (known as ICAFA) is a modified form of the ICA algorithm based on the firefly algorithm. This modification results in an increase in the exploratory capability of the algorithm and improvement of its convergence rate. This inversion technique was first successfully tested on a synthetic gravity anomaly originated from a simulated sedimentary basin model both with and without the presence of white Gaussian noise (WGN). At last, the method was applied to the Bouguer anomaly from a real gravity profile in Moghan sedimentary basin (Iran). The results of this modeling were compatible with previously published works which consisted of both seismic analysis and other gravity interpretations. In order to estimate the uncertainty of solutions, several inversion runs were also conducted independently and the results were in line with the final solution.

2

Modified blind naked mole-rat algorithm applied to electromagnetic design problems

Taherdangkoo Mohammad

Archives of Electrical Engineering

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2021

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Vol. 70, nr 2

167--380

EN

In this paper,we proposed a modified meta-heuristic algorithm based on the blind naked mole-rat (BNMR) algorithm to solve the multiple standard benchmark problems. We then apply the proposed algorithm to solve an engineering inverse problem in the electromagnetic field to validate the results. The main objective is to modify the BNMR algorithm by employing two different types of distribution processes to improve the search strategy. Furthermore, we proposed an improvement scheme for the objective function and we have changed some parameters in the implementation of the BNMR algorithm. The performance of the BNMR algorithm was improved by introducing several new parameters to find the better target resources in the implementation of a modified BNMR algorithm. The results demonstrate that the changed candidate solutions fall into the neighborhood of the real solution. The results show the superiority of the propose method over other methods in solving various mathematical and electromagnetic problems.

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An efficient parallel global optimization strategy based on Kriging properties suitable for material parameters identification

Roux Emile, Tillier Yannick, Kraria Salim, Bouchard Pierre-Olivier

Archive of Mechanical Engineering

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2020

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LXVII, nr 2

169--195

EN

Material parameters identification by inverse analysis using finite element computations leads to the resolution of complex and time-consuming optimization problems. One way to deal with these complex problems is to use meta-models to limit the number of objective function computations. In this paper, the Efficient Global Optimization (EGO) algorithm is used. The EGO algorithm is applied to specific objective functions, which are representative of material parameters identification issues. Isotropic and anisotropic correlation functions are tested. For anisotropic correlation functions, it leads to a significant reduction of the computation time. Besides, they appear to be a good way to deal with the weak sensitivity of the parameters. In order to decrease the computation time, a parallel strategy is defined. It relies on a virtual enrichment of the meta-model, in order to compute q new objective functions in a parallel environment. Different methods of choosing the qnew objective functions are presented and compared. Speed-up tests show that Kriging Believer (KB) and minimum Constant Liar (CLmin) enrichments are suitable methods for this parallel EGO (EGO-p) algorithm. However, it must be noted that the most interesting speed-ups are observed for a small number of objective functions computed in parallel. Finally, the algorithm is successfully tested on a real parameters identification problem.

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O kilku osobliwościach w oddziaływaniach molekuł

Piela L.

Wiadomości Chemiczne

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2011

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[Z] 65, 11-12

935-952

EN

The ground state electronic energy represents a complicated function of the nuclear coordinates. Even for relatively small molecules this function may have many minima in the corresponding "energy landscape", very often myriads of minima, each of them corresponding to a stable configuration of the nuclei. This is why predicting the lowest-energy conformation or configuration represents a formidable task. There were many attempts to solve this problem for protein molecules, for which it is believed their native conformation corresponds to the lowest free energy. The challenge to find this conformation from a given sequence of amino acids is known as a "second genetic code". In fact all of these attempts based on some smoothing of the energy landscape. In the article some of these smoothing techniques are described, from a generic one to those, which finally turned out to be highly successful in finding native structures of globular proteins. When discussing the contributions to the conformational energy the importance of the hydrophobic effect as well as of the electrostatic interactions has been stressed. In particular it turned out that the dipole moments of the NH and of the CO bonds in proteins functioning in nature are oriented to good accuracy along the local intramolecular electric field. Thanks to enormous effort of the protein folding community it is possible to design such amino acid sequences, which fold to the desired protein 3D structure. A certain reliable theoretical technique of protein folding has been used to study a possibility of conformational autocatalysis. It turned out that a small protein of 32 amino acids, with carefully predesigned amino acid sequence, exhibits indeed such an effect, which may be seen as a model of the prion disease propagation.