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Optimal Filter Design Using differential evolution algorithm and Its Advanced Variants

CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2025年

作者： Durmus, Burhanettin Unlu, Aybuke Ozyon, Serdar Temurtas, Hasan Kutahya Dumlupinar Univ Dept Elect & Elect Engn Kutahya Turkiye Kutahya Dumlupinar Univ Dept Comp Engn Kutahya Turkiye

Since passive elements such as resistors and capacitors used in active filter design change the gain and phase of the filter, their selection is an important issue. The ability of the filter to achieve a targeted quality factor depends on the selection of these components. The filter sections are cascaded to get closer to the ideal filter response;in this case, as the number of components increases, the computational complexity in selecting the optimum values increases. Moreover, in practical applications, the values of the filter components should be fixed to the discrete component values in the industrial component series. Thus, the problem turns into a discrete optimization problem that becomes more difficult and time-consuming. The use of metaheuristic algorithms in solving the problem is an alternative approach. This work propounds a survey on the differential evolution (DE) algorithm and its advanced variants utilized for the selection of optimal component values in filter design. Nine DE algorithms have been used to determine the optimal component values of the tenth-order Multi-Feedback topology Bessel filter. The performance of each algorithm has been evaluated in terms of convergence rate and solution accuracy. Statistical results show that success-history based adaptive DE with linear population size reduction (LSHADE) is superior to other DE variants and can reduce the filter quality factor error value to 4.64E-02 for E12 series, 6.45E-02 for E96 series and 2.23E-02 for E192 series. The obtained results show that LSHADE algorithm are an effective tool for the selection of optimal discrete component values in filter design, increasing computational speed and solution accuracy.

关键词： Active filter design Bessel filter differential evolution algorithm Multiple feedback topology

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Deep Integration of English Information Teaching Based on differential evolution algorithm

International Journal of Social Science and Education Resear...

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International Journal of Social Science and Education Research 2023年第8期6卷 144-150页

作者： Lin Yang

Modern information technology is becoming more and more mature and the use of multimedia such as computers is becoming more and more popular. English teaching in our country's undergraduate colleges is also developing in line with the times, and information‐based teaching represented by information technology means such as computers and multimedia has gradually emerged. The purpose of this paper is to analyze the impact based on differential evolution algorithms and to develop an effective approach to English language learning, with a focus on improving the quality of education for undergraduate students. By collecting, sorting and reading related journals and publications, using the method of query research, based on the variance evolution algorithm, the differential learning research based on the English algorithm algorithm is carried out for the students of the two optional classes in high school. The survey results show that 63.2% of the respondents believe that learning English based on different evolutionary algorithms may stimulate their interest in writing. In addition, the comparison of the results of classroom experiments and classroom control shows that 95% of the respondents believe that the differential evolution algorithm is applied to English computer science, and English learning with some technologies will be improved.

关键词： differential evolution algorithm English Teaching Information‐based Teaching Deep Integration

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Okumura Hata Propagation Model Optimization in 400 MHz Band Based on differential evolution algorithm: Application to the City of Bertoua

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Journal of Computer and Communications 2023年第5期11卷 52-69页

作者： Eric Michel Deussom Djomadji Ivan Basile Kabiena Joel Thibaut Mandengue Felix Watching Emmanuel Tonye Department of Electrical and Electronic Engineering College of Technology University of Buea Buea Cameroon Division of ICT National Advanced School of Post Telecommunication and ICT University of Yaounde I Yaounde Cameroon Department of Computer Engineering and Telecommunications National Advanced School of Engineering University of Douala Douala Cameroon Department of Electrical and Telecommunications Engineering National Advanced School of Engineering of Yaounde University of Yaounde I Yaounde Cameroon

Propagation models are the foundation for radio planning in mobile networks. They are widely used during feasibility studies and initial network deployment, or during network extensions, particularly in new cities. They can be used to calculate the power of the signal received by a mobile terminal, evaluate the coverage radius, and calculate the number of cells required to cover a given area. This paper takes into account the standard k factors model and then uses the differential evolution algorithm to set up a propagation model adapted to the physical environment of the Cameroonian cities of Bertoua. Drive tests were made on the LTE TDD network in the city of Bertoua. differential evolution algorithm is used as the optimization algorithm to deduct a propagation model which fits the environment of the considered town. The calculation of the root mean square error between the actual data from the drive tests and the prediction data from the implemented model allows the validation of the obtained results. A comparative study made between the RMSE value obtained by the new model and those obtained by the Okumura Hata and free space models, allowed us to conclude that the new model obtained is better and more representative of our local environment than the Okumura Hata currently used. The implementation shows that differential evolution can perform well and solve this kind of optimization problem;the newly obtained models can be used for radio planning in the city of Bertoua in Cameroon.

关键词： Radio Measurements Root Mean Square Error differential evolution algorithm

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Improved Adaptive differential evolution algorithm for the Un-Capacitated Facility Location Problem

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Open Journal of Applied Sciences 2023年第5期13卷 685-695页

作者： Nan Jiang Huizhen Zhang Business School University of Shanghai for Science and Technology Shanghai China

The differential evolution algorithm is an evolutionary algorithm for global optimization and the un-capacitated facility location problem (UFL) is one of the classic NP-Hard problems. In this paper, combined with the specific characteristics of the UFL problem, we introduce the activation function to the algorithm for solving UFL problem and name it improved adaptive differential evolution algorithm (IADEA). Next, to improve the efficiency of the algorithm and to alleviate the problem of being stuck in a local optimum, an adaptive operator was added. To test the improvement of our algorithm, we compare the IADEA with the basic differential evolution algorithm by solving typical instances of UFL problem respectively. Moreover, to compare with other heuristic algorithm, we use the hybrid ant colony algorithm to solve the same instances. The computational results show that IADEA improves the performance of the basic DE and it outperforms the hybrid ant colony algorithm.

关键词： Un-Capacitated Facility Location Problem differential evolution algorithm Adaptive Operator

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Calibration of Offsets in Time-Interleaved ADCs in an OFDM Receiver Using differential evolution algorithm

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OPTOELECTRONICS INSTRUMENTATION AND DATA PROCESSING 2021年第3期57卷 287-296页

作者： Chakravarthi, M. V. N. Chandramohan, Dr B. Acharya Nagarjuna Univ Dept ECE Nagarjuna Nagar 522510 Andhra Pradesh India Bapatla Engn Coll Dept ECE Bapatla 522101 India

Time-interleaved analog-to-digital converters (TIADCs) are used when high sampling rates are required. However, TIADCs have offsets such as sampling time, gain, dc, and phase offsets. Due to these offsets, the reconstructed signal from TIADCs is erroneous. Hence, these offsets should be estimated and then corrected. The proposed work focuses on estimation and correction of the offsets. For estimation of offsets differential evolution optimization algorithm is used, and correction is applied using the estimated offsets. Estimation is evaluated by finding BER (bit error rate) and SNDR (signal-to-noise and distortion ratio). The estimation and correction is implemented for 7 and 8-channel TIADCs in an OFDM system with 4-QPSK modulation. The technique is evaluated by applying monotonic sinusoidal and image signals to the OFDM system.

关键词： time-interleaved ADC differential evolution algorithm orthogonal frequency division multiplexing (OFDM) bit error rate (BER)

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differential evolution algorithm based on PCA to determine the objective function to optimize the configuration of microgrid

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Journal of Physics: Conference Series 2021年第1期2003卷

作者： Wang, Yunhu Xu, Ruobing Duan, Qing Zhang, Guobao Huang, Yongming Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University Nanjing210096 China State Grid Jiangsu Electric Power Co. Ltd. Nanjing Power Supply Branch Nanjing210019 China China Electric Power Research Institute Co. Ltd. Beijing100192 China

Recently, microgrids are increasingly used in our lives. The purpose of this paper is to solve the uncertainties of multi-objective decision-making and the instability of algorithms in the optimal configuration of traditional microgrids. This paper proposed a differential evolution algorithm based on PCA to determine the objective function. Firstly, a multi-objective optimization model of the micro-grid was established on the basis of fully considering the economy, environmental protection and stability of the micro-grid. Next, the first principal component of the multi-objective was extracted based on PCA combining innovatively the Pareto optimal solution set, and the multi-objective optimization problem was transformed into a single-objective optimization problem. Finally, the experimental simulation result shows that the algorithm proposed in this paper can comprehensively consider the economy, environmental protection and stability of the microgrid on the basis of ensuring the efficiency and stability of the algorithm to realize the optimized configuration of the microgrid. © Published under licence by IOP Publishing Ltd.

关键词： differential evolution algorithm microgrid Pareto optimal solution set PCA

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

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FOUNDATIONS OF COMPUTING AND DECISION SCIENCES 2023年第2期48卷 243-266页

作者： Singsathid, Pirapong Puphasuk, Pikul Wetweerapong, Jeerayut Khon Kaen Univ Fac Sci Deparment Math Khon Kaen 40002 Thailand

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 probabilities 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.

关键词： differential evolution algorithm ant colony optimization pheromone strategy optimization

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Transit Frequency Optimization in Bi-modal Networks Using differential evolution algorithm

TEKNIK DERGI

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TEKNIK DERGI 2022年第5期33卷 12601-12616页

作者： Mutlu, Mehmet Metin Aksoy, Ilyas Cihan Alver, Yalcin Adnan Menderes Univ Dept Civil Engn Aydin Turkey Karamanoglu Mehmetbey Univ Dept Civil Engn Karaman Turkey Ege Univ Dept Civil Engn Izmir Turkey

This study proposes a bi-level optimization model for the transit frequency setting problem in bi-modal networks. The objective of the upper-level problem is to obtain a solution set of bus line frequencies that provide the minimum total travel cost of the car and bus users. differential evolution (DE) algorithm is employed in the upper-level model to determine the optimal headways for a given route structure. The lower-level model is a congested multi-modal user equilibrium assignment model, which considers the interactions of car and bus flows, for determining joint mode/route preferences of the network users, which considers the interactions of car and bus flows. The developed model is tested on Mandl's benchmark network to evaluate its performance and applicability. The comparative experiments demonstrate that the proposed model leads to reductions in transportation costs. Also, the result of numerous optimization runs shows that DE performs well in finding similar frequency sets in independent optimizations.

关键词： Transit frequency setting problem bus frequency optimization multi-modal assignment differential evolution algorithm bi-level optimization

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An Interactive differential evolution algorithm Based on Backtracking Strategy Applied in Interior Layout Design

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algorithmS 2023年第6期16卷 275-275页

作者： Yu, Fei Liang, Bang Tang, Bo Wu, Hongrun Minnan Normal Univ Sch Phys & Informat Engn Zhangzhou 363000 Peoples R China Minnan Normal Univ Sch Comp Sci Zhangzhou 363000 Peoples R China

The Interior layout model is to optimize the arrangement position of each room to maximize the comfort and quality of life of residents. Due to the complexity of the Interior layout problem, the computation of fitness function costs lots of time. To reduce the high computational cost while maintaining the solution performance. An interactive differential evolution algorithm based on Backtracking operator (IDE-BO) is proposed as the solver of the Interior layout model. The human-computer interaction mechanism of IDE benefits the automatic adjustment of fitness parameters that best meet the user's subjective preferences to achieve the optimal solution. At the same time, the backtracking strategy can also help jump out when the algorithm falls into local optimization. The IDE is compared to other two conventional optimization methods based on two different layout scenarios. The experimental results show that in interior layout model IDE-BO is better than conventional interactive genetic algorithm (IGA) and IDE which do not use BO strategy, the super-performance of IDE-BO in complex situations in terms of execution time and convergence rate.

关键词： interactive evolutionary algorithm differential evolution algorithm interior design spatial distribution

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Inverse Kinematics Study for Intelligent Agriculture Robot Development via differential evolution algorithm

Inverse Kinematics Study for Intelligent Agriculture Robot D...

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International Conference on Computer, Control and Robotics (ICCCR)

作者： Li, Chen Dong, Hui Li, Xubing Zhang, Weikang Liu, Xiaodong Yao, Ligang Sun, Hao Fuzhou Univ Coll Mech Engn & Automat Fuzhou Peoples R China Fujian Prov Collaborat Innovat Ctr High End Equip Fuzhou 350001 Peoples R China

ISBN: (纸本)9781728190358

Robots with intelligent moving and manipulating ability are able to improve productivity of agriculture work. We prototyped a mobile robot equipped with reductant manipulator (7-DOF). Here, for controlling the manipulator precisely, we investigate the inverse kinematics (IK) issue of the manipulator. A novel IK solving method by adopting an improved differential evolution algorithm has been validated. Also, random change crossover is employed to restrict the tendency of falling into local optimization when we use the algorithm. In parallel, considering the position and posture errors, boundary processing has been redesigned for avoiding joint limits. Thereafter, we obtain the global optimal IK solutions. Simulation tests have been carried out using the numerical model of the redundant arm. By testing accuracy and stability of the arm, we verify the feasibility and efficiency of the proposed approach.

关键词： intelligent agriculture robot redundant arm inverse kinematics differential evolution algorithm

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