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1

Synthesis of Reconfigurable Multiple Shaped Beams of a Concentric Circular Ring Array Antenna Using Evolutionary Algorithms

Dubey Sanjay Kumar, Mandal Debasis

Journal of Telecommunications and Information Technology

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2023

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nr 1

8--17

EN

The approach described in this paper uses evolutionary algorithms to create multiple-beam patterns for a concentric circular ring array (CCRA) of isotropic antennas using a common set of array excitation amplitudes. The flat top, cosec2, and pencil beam patterns are examples of multiple-beam patterns. All of these designs have an upward angle of θ = 0◦. All the patterns are further created in three azimuth planes (φ = 0◦, 5◦, and 10◦). To create the necessary patterns, non-uniform excitations are used in combination with evenly spaced isotropic components. For the flat top and cosecant-squared patterns, the best combination of common components, amplitude and various phases is applied, whereas the pencil beam pattern is produced using the common amplitude only. Differential evolutionary algorithm (DE), genetic algorithm (GA), and firefly algorithm (FA) are used to generate the best 4-bit discrete magnitudes and 5-bit discrete phases. These discrete excitations aid in lowering the feed network design complexity and the dynamic range ratio (DRR). A variety of randomly selected azimuth planes are used to verify the excitations as well. With small modifications in the desired parameters, the patterns are formed using the same excitation. The results proved both the efficacy of the suggested strategy and the dominance of DE over GA as well as FA.

2

Adaptive differential evolution algorithm with a pheromone-based learning strategy for global continuous optimization

Singsathid Pirapong, Puphasuk Pikul, Wetweerapong Jeerayut

Foundations of Computing and Decision Sciences

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2023

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Vol. 48, No. 2

243--266

EN

Differential evolution algorithm (DE) is a well-known population-based method for solving continuous optimization problems. It has a simple structure and is easy to adapt to a wide range of applications. However, with suitable population sizes, its performance depends on the two main control parameters: scaling factor (F) and crossover rate (CR). The classical DE method can achieve high performance by a time-consuming tunning process or a sophisticated adaptive control implementation. We propose in this paper an adaptive differential evolution algorithm with a pheromone-based learning strategy (ADE-PS) inspired by ant colony optimization (ACO). The ADE-PS embeds a pheromone-based mechanism that manages the prob- abilities associated with the partition values of F and CR. It also introduces a resetting strategy to reset the pheromone at a specific time to unlearn and relearn the progressing search. The preliminary experiments find a suitable number of subintervals (ns) for partitioning the control parameter ranges and the reset period (rs) for resetting the pheromone. Then the comparison experiments evaluate ADE-PS using the suitable ns and rs against some adaptive DE methods in the literature. The results show that ADE-PS is more reliable and outperforms several well-known methods in the literature.

3

Multiple Droop-Controlled DG Sites in an Islanded AC Microgrid for Power Losses Mitigation

Nguyen Tham X., Lis Robert

Automatyka, Elektryka, Zakłócenia

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2023

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Vol. 14, nr 2(52)

10--24

EN

This study investigates the installation of multiple droop-controlled distributed generator (DG) sites in an Autonomous Microgrid (AMG) to mitigate power losses. The methodology employs a differential evolution algorithm integrated with a modified backward-forward sweep load flow method to optimise the DG sizing and positioning. Tested on an IEEE 33-bus AMG, the results show a significant reduction in power losses with multiple DG placements, highlighting the potential to improve microgrid performance.

PL

Przedstawiono analizę umiejscowienia generatorów rozproszonych (DG) w izolowanej mikrosieci (AMG), z regulowanym statyzmem oraz z rozwiniętą strukturą hierarchiczną w celu redukcji strat mocy. Metoda wykorzystuje algorytm ewolucji różnicowej zintegrowany z modyfikowaną metodą rozpływu mocy w celu optymalizacji rozmiaru i pozycjonowania DG. Przetestowane na 33-węzłowej mikrosieci testowej IEEE wyniki ukazują znaczącą redukcję strat mocy dzięki optymalnym lokalizacjom DG, wskazują na potencjał poprawy wydajności pracy mikrosieci.

4

Lokalizacja źródeł rozproszonych z regulowanym statyzmem w izolowanej mikrosieci : minimalizująca straty mocy

Nguyen Tham X., Lis Robert

Automatyka, Elektryka, Zakłócenia

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2023

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Vol. 14, nr 2(52)

26--41

PL

Przedstawiono analizę umiejscowienia generatorów rozproszonych (DG) w izolowanej mikrosieci (AMG), z regulowanym statyzmem oraz z rozwiniętą strukturą hierarchiczną w celu redukcji strat mocy. Metoda wykorzystuje algorytm ewolucji różnicowej zintegrowany z modyfikowaną metodą rozpływu mocy w celu optymalizacji rozmiaru i pozycjonowania DG. Przetestowane na 33-węzłowej mikrosieci testowej IEEE wyniki ukazują znaczącą redukcję strat mocy dzięki optymalnym lokalizacjom DG, wskazują na potencjał poprawy wydajności pracy mikrosieci.

EN

This study investigates the installation of multiple droop-controlled distributed generator (DG) sites in an Autonomous Microgrid (AMG) to mitigate power losses. The methodology employs a differential evolution algorithm integrated with a modified backward-forward sweep load flow method to optimise the DG sizing and positioning. Tested on an IEEE 33-bus AMG, the results show a significant reduction in power losses with multiple DG placements, highlighting the potential to improve microgrid performance.

5

Control Strategy of Parallel Systems with Efficiency Optimisation in Switched Reluctance Generators

Zan Xiaoshu, Lin Hang, Xu Guanqun, Zhao Tiejun, Gong Yi

Power Electronics and Drives

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2021

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Vol. 6 (41)

61--74

EN

To solve motor heating and life shortening of parallel switched reluctance generator (SRG) induced by uneven output currents due to different external characteristics, we generally adopt current sharing control (CSC) to make each parallel generator undertake large load currents on average to improve the reliability of parallel power generation system. However, the method usually causes additional loss of power because it does not consider the efficiency characteristics of each parallel generator. Therefore, with the efficiency expression for the parallel system of SRG established and analysed, the control strategy based on differential evolution (DE) algorithm is proposed as a mechanism by which to enhance generating capacity and reliability of multi-machine power generation from the perspective of efficiency optimisation. We re-adjust the reference current of each parallel generator to transform the working point of each generator and implement the efficiency optimisation of parallel system. The performance of the proposed control method is evaluated in detail by the simulation and experiment, and comparison with traditional CSC is carried out as well.

6

Combination of the Levenberg–Marquardt and diferential evolution algorithms for the ftting of postseismic GPS time series

Li Jingwei, Zhan Wei, Guo Bofeng, Li Shuiping, Guo Binghui

Acta Geophysica

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2021

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Vol. 69, no. 2

405--414

EN

Postseismic global positioning system (GPS) time series are of fundamental importance for investigating the physical mechanisms of postseismic deformations, as well as the construction and maintenance of terrestrial reference frames. Particularly, methods for constructing accurate ftting models for such time series are critical. Based on the physical features of postseismic deformation models, we propose a new algorithm that combines the strengths of the Levenberg–Marquardt (LM) and dif ferential evolution (DE) algorithms, that is, the LM+DE algorithm. In this algorithm, the parameters are initialised by the constrained DE algorithm; the fnal parameters of the postseismic model are then solved by the LM algorithm. To validate the proposed method, DE, LM, and LM+DE were compared using synthetic and observational data from the 2011 Tohoku Earthquake. For all tests based on synthetic data, the LM+DE algorithm consistently converged to the global solution and the residual is small, regardless of how the independent parameter was varied. In the 2011 Tohoku earthquake, the parameters calculated by the LM+DE algorithm matched consistently for the global solution with a 100% passing rate after constraints were provided for the ratios of the initial relaxation time parameters. In contrast, the LM and DE algorithms individually achieved passing rates of only 22% and 1%, respectively. These results demonstrate that the proposed LM+DE algorithm efectively solves the initial estimate problem in the ftting of nonlinear postseismic models, and also ensures that the fts are mathematically optimal and consistent with physical reality.

7

Adaptive Differential Evolution with Elite Opposition-Based Learning and its Application to Training Artificial Neural Networks

Choi Tae Jong, Lee Jong-Hyun, Youn Hee Yong, Ahn Chang Wook

Fundamenta Informaticae

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2019

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Vol. 164, nr 2-3

227--242

EN

Differential Evolution (DE) algorithm is one of the popular evolutionary algorithms that is designed to find a global optimum on multi-dimensional continuous problems. In this paper, we propose a new variant of DE algorithm by combining a self-adaptive DE algorithm called dynNP-DE with Elite Opposition-Based Learning (EOBL) scheme. Since dynNP-DE algorithm uses a small number of population size in the later of the search process, the population diversity becomes low, and therefore premature convergence may occur. We have therefore extended an OBL scheme to dynNP-DE algorithm to overcome this shortcoming and improve the optimization performance. By combining EOBL scheme to dynNP-DE algorithm, the population diversity can be supplemented because not only the information of individuals but also their opposition information can be utilized. We measured the optimization performance of the proposed algorithm on CEC 2005 benchmark problems and breast cancer detection, which is a research field that has recently attracted a lot of attention. It was verified that the proposed algorithm could find better solutions than five state-of-the-art DE algorithms.

8

A hybrid method for blood vessel segmentation in images

Díaz Primitivo, Rodríguez Alma, Cuevas Erik, Valdivia Arturo, Chavolla Edgar, Pérez-Cisneros Marco, Zaldívar Daniel

Biocybernetics and Biomedical Engineering

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2019

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Vol. 39, no. 3

814--824

EN

In the last years, image processing has been an important tool for health care. The analysis of retinal vessel images has become crucial to achieving a better diagnosis and treatment for several cardiovascular and ophthalmological deceases. Therefore, an automatic and accurate procedure for retinal vessel and optic disc segmentation is essential for illness detection. This task is extremely hard and time-consuming, often requiring the assistance of human experts with a high degree of professional skills. Several retinal vessel segmentation methods have been developed with satisfactory results. Nevertheless, most of such techniques present a poor performance mainly due to the complex structure of vessels in retinal images. In this paper, an accurate methodology for retinal vessel and optic disc segmentation is presented. The proposed scheme combines two different techniques: the Lateral Inhibition (LI) and the Differential Evolution (DE). The LI scheme produces a new image with enhanced contrast between the background and retinal vessels. Then, the DE algorithm is used to obtain the appropriate threshold values through the minimization of the cross-entropy function from the enhanced image. To evaluate the performance of the proposed approach, several experiments over images extracted from STARE, DRIVE, and DRISHTI-GS databases have been conducted. Simulation results demonstrate a high performance of the proposed scheme in comparison with similar methods reported in the literature.

9

Comparison of different approaches in traffic forecasting models for the D-200 highway in Turkey

Dogan E., Korkmaz E., Akgungor A. P.

Zeszyty Naukowe. Transport / Politechnika Śląska

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2018

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z. 99

25--42

EN

Short-term traffic estimations have a significant influence in terms of effectively controlling vehicle traffic. In this study, short-term traffic forecasting models have been developed based on different approaches. Seasonal autoregressive integrated moving average (SARIMA), artificial bee colony (ABC) and differential evolution (DE) algorithms are the techniques used in the optimization of models, which have been developed by using observation data for the D-200 highway in Turkey. 80% of the data were used for training, with the remaining data used for testing. The performances of the models were illustrated with mean absolute errors (MAEs), mean absolute percentage errors (MAPEs), the coefficient of determination (R2) and the root-mean-square errors (RMSEs). It is understood that all the models provided consistent and useful results when the developed models were compared with the statistical results. In the models created separately for two lanes, the R2 values of the models were calculated to be approximately 92% for the right lane, which is generally used by heavy vehicles, and 88% for the left lane, which is used by less traffic. Based on the MAE and RMSE values, the model developed by the ABC algorithm gave the lowest error and showed more effective performance than the other approaches. Thus, the ABC model showed that it is appropriate for use on other highways in Turkey.

10

Optimum design of fiber angle and hole orientation of an orthotropic plate

Zhang X., Lu A., Wang S., Zhang N.

Journal of Theoretical and Applied Mechanics

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2018

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Vol. 56 nr 1

297--311

EN

With the goal of decreasing the stress concentration along the hole boundary in an orthotropic plate under inequi-biaxial loadings, an optimum design of the fiber angle and hole orientation is presented. The maximum absolute tangential stress along the hole boundary is taken as the objective function, and the fiber orientation angle and the hole orientation angle are considered as design variables. The conformal transformation method of a complex function and the Differential Evolution (DE) algorithm are used. Two non-circular shapes, ellipse and hexagon are taken as examples to analyze the problem. Based on the results, we can conclude that the major axis of elliptical holes should be designed in the direction of the maximum external loading for a perforated structure in an orthotropic plate. However, the principal direction that has the larger Young’s modulus should be inclined to the direction of the minimum loading, especially for a significantly orthotropic plate.

11

Intelligent hybrid fuzzy logic system for damage detection of beam-like structural elements

Sahu S., Kumar P. B., Parhi D. R.

Journal of Theoretical and Applied Mechanics

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2017

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Vol. 55 nr 2

509--521

EN

Fuzzy logic has been used in different research fields for more than three decades. It has become a robust method to solve complex and intricate problems which are otherwise difficult to solve by traditional methods. But it still requires some human experience and knowledge. In the present study, an attempt is made to design a hybrid optimization technique for automatic formation of the fuzzy knowledge based rules using an evolutionary algorithm. This hybridization technique has been applied in the field of damage detection and location of cracks in cracked structural elements. In this paper, a robust fault diagnostic tool based on a differential evolution algorithm and fuzzy logic has been proposed. Theoretical and Finite Element analyzes are done to model the crack and to find the effect of the presence of cracks on changes of vibrational characteristic (natural frequencies) of a fixed-fixed beam. The inputs to DEA-FL system are the first three relative natural frequencies, and the outputs from the system are the relative crack depth and relative crack location. For the validation of the results obtained from the proposed method and to check the robustness of the controller, experimental analysis is performed. To find average error rates, the bootstrap method has been adopted.

12

Solution of singular optimal control problems using the improved differential evolution algorithm

Lobato F. S., Steffen, Jr V., Silva Neto A. J.

Journal of Artificial Intelligence and Soft Computing Research

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2011

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Vol. 1, No. 3

195--206

EN

The Differential Evolution algorithm, like other evolutionary techniques, presents as main disadvantage the high number of objective function evaluations as compared with classical methods. To overcome this disadvantage, this work proposes a new strategy for the dynamic updating of the population size to reduce the number of objective function evaluations. This strategy is based on the definition of convergence rate to evaluate the homogeneity of the population in the evolutionary process. The methodology is applied to the solution of singular optimal control problems in chemical and mechanical engineering. The results demonstrated that the methodology proposed represents a promising alternative as compared with other competing strategies.

13

Design of IIR digital filters with non-standard characteristics using differential evolution algorithm

Słowik A., Białko M.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2007

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Vol. 55, nr 4

359-363

EN

In the paper an application of differential evolution algorithm to design digital filters with non-standard amplitude characteristics is presented. Three filters with characteristics: linearly growing, linearly falling, and non-linearly growing are designed with the use of the proposed method. The digital filters obtained using this method are stable, and their amplitude characteristics fulfill all design assumptions.