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1

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

Definition of Mass Spring Parameters for Knitted Fabric Simulation Using the Imperialist Competitive Algorithm

Mozafary V., Payvandy P.

Fibres & Textiles in Eastern Europe

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2017

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Vol. 25, no. 1 (121)

65--74

EN

The 3D simulation of fabrics is an interesting issue in many fields, such as computer engineering, textile engineering, cloth design and so on. Several methods have been presented for fabric simulation. The mass spring model, a typical physically-based method, is one of the methods for fabric simulation which is widely considered by researchers due to rapid simulation and being more consistent with reality. The aim of this paper is the optimization of mass spring parameters in the simulation of the drape behaviour of knitted fabric using the Imperialist Competitive Algorithm. First a mass spring model is proposed to simulate the drape behavior of knitted fabric. Then in order to reduce the error value between the simulated and actual result (reducing the simulation error value), parameters of the mass spring model such as the stiffness coefficient, damping coefficient, elongation rate, topology and natural length of the spring are optimized using the Imperialist Competitive Algorithm (ICA). The ICA parameters are specified using the Taguchi Design of Experiment. Finally fabrics drape shapes are simulated in other situations and compared with their actual results to validate the model parameters. Results show that the optimized model is able to predict the drape behavior of knitted fabric with an error value of 2.4 percent.

PL

Celem niniejszej pracy jest optymalizacja parametrów masowo-sprężystych w symulacji układalności struktur dzianych przy wykorzystaniu imperialistycznego algorytmu konkurencji. Zaproponowano model mas i sprężyn symulujących zachowanie dzianin. Następnie, dla polepszenia korelacji pomiędzy strukturami teoretycznymi a rzeczywistymi, określone parametry modelu, takie jak: współczynnik sztywności, współczynnik tłumienia, wydłużenie, topologia i naturalna długości sprężyny zoptymalizowano posługując się imperialistycznym algorytmem konkurencji (ICA). Parametry określono przy użyciu planowania eksperymentu metodą Taguchi. Przedstawiono i porównano symulacje układalności z rzeczywistą układalnością dzianin. Stwierdzono, że opracowany model pozwala na przewidywanie układalności dzianin z dokładnością do 2,4%.

3

A framework for optimal clustering of a greenfield distribution network area into multiple autonomous microgrids

Mojtahedzadeh S., Najafi Ravadanegh S., Haghifan M. R.

Journal of Power Technologies

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2016

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Vol. 96, nr 4

219--228

EN

Microgrids (MGs) are recognized as cores and clusters of smart distribution networks. The optimal planning and clustering of smart low-voltage distribution networks into autonomous MGs within a greenfield area is modeled and discussed in this paper. In order to form and determine the electrical boundary of MGs set, some predefined criteria such as power mismatch, supply security and load density are defined. The network includes an external grid as backup and both dispatchable and non-dispatchable Distributed Energy Resources (DERs) as MGs resources. The proposed strategy offers optimum sizing and siting of DERs and MV substations for the autonomous operation of multiple MGs simultaneously. The imperialist competitive algorithm (ICA) is used to optimize the cost function to determine the optimal linked MG clustering boundary. To evaluate the algorithm the proposed method is applied to a greenfield area which is planned to become a mixed residential and commercial town. The MGs’ optimal border, DERs location, size and type within each MG and LV feeders route are illustrated in both graphical and tabular form.