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Time-varying external archive differential evolution algorithm with applications to parallel mechanisms

APPLIED MATHEMATICAL MODELLING 2023年 114卷 745-769页

作者： Wen, Shikun Ji, Aihong Che, Linxian Yang, Zhikang Nanjing Univ Aeronaut & Astronaut Coll Mech & Elect Engn Lab Locomot Bioinspirat & Intelligent Robots 29 Yudao St Nanjing 210016 Jiangsu Peoples R China Chongqing Vocat Inst Engn Sch Intelligence Mfg & Traff 1 Nanbei Ave Chongqing 402260 Peoples R China

In this work, a time-varying external archive differential evolution algorithm is proposed, which can obtain the multiple roots for system of nonlinear equations for the forward dis-placement of parallel mechanisms. In time-varying external archive differential evolution three improvements are presented. At first, a time-varying subpopulation strategy is pro-posed to consider both global and local searching capabilities. Then, an individual judg-ment criterion is proposed, which employs the weighted basis vector mutation strategy for ordinary individuals and a hybrid mutation operator for locally optimal individuals. Fi-nally, the external archive strategy of neighborhood-based crowding differential evolution is improved to enhance the domain searching ability of the algorithm. To evaluate the per-formance of time-varying external archive differential evolution, twenty benchmark func-tions are selected as the test suite. Moreover, the solutions for forward displacements of four strongly coupled parallel mechanisms with different degrees of freedom are derived to test the generality of this method. From the acquired experimental results, it is demon-strated that fairly-competitive results can be provided compared to other methods, in both benchmark functions and forward displacement solutions of parallel mechanisms. (C) 2022 Elsevier Inc. All rights reserved.

关键词： Parallel mechanism Forward displacement solutions differential evolution algorithm Time-varying subpopulations Individual judgment External archive

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Parameter estimation of Wiener-Hammerstein system based on multi-population self-adaptive differential evolution algorithm

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ENGINEERING COMPUTATIONS 2023年第9/10期40卷 2248-2269页

作者： Chu, Jie Li, Junhong Jiang, Yizhe Song, Weicheng Zong, Tiancheng Nantong Univ Sch Elect Engn Nantong Peoples R China

PurposeThe Wiener-Hammerstein nonlinear system is made up of two dynamic linear subsystems in series with a static nonlinear subsystem, and it is widely used in electrical, mechanical, aerospace and other fields. This paper considers the parameter estimation of the Wiener-Hammerstein output error moving average (OEMA) ***/methodology/approachThe idea of multi-population and parameter self-adaptive identification is introduced, and a multi-population self-adaptive differential evolution (MPSADE) algorithm is proposed. In order to confirm the feasibility of the above method, the differential evolution (DE), the self-adaptive differential evolution (SADE), the MPSADE and the gradient iterative (GI) algorithms are derived to identify the Wiener-Hammerstein OEMA system, *** the simulation results, the authors find that the estimation errors under the four algorithms stabilize after 120, 30, 20 and 300 iterations, respectively, and the estimation errors of the four algorithms converge to 5.0%, 3.6%, 2.7% and 7.3%, which show that all four algorithms can identify the Wiener-Hammerstein OEMA ***/valueCompared with DE, SADE and GI algorithm, the MPSADE algorithm not only has higher parameter estimation accuracy but also has a faster convergence speed. Finally, the input-output relationship of laser welding system is described and identified by the MPSADE algorithm. The simulation results show that the MPSADE algorithm can effectively identify parameters of the laser welding system.

关键词： Wiener-Hammerstein Nonlinear system identification differential evolution algorithm Multi-population Self-adaptive

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Investigation on small volume and long optical path multipass cell using differential evolution algorithm

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MICROWAVE AND OPTICAL TECHNOLOGY LETTERS 2023年第5期65卷 1372-1378页

作者： Zhang, Mengru Chen, Chen Chen, Hongda Dong, Weihao Li, Yongyang Xu, Haozhi Li, Chunguang Jilin Univ Coll Instrumentat & Elect Engn Changchun Peoples R China Jilin Univ Coll Biol & Agr Engn Changchun 130022 Peoples R China Jilin Univ Coll Instrumentat & Elect Engn Key Lab Geophys Explorat Equipment Minist Educ China Changchun 130026 Peoples R China

To solve the contradiction between high performance and portability of tunable diode laser absorption spectroscopy (TDLAS) systems, we propose a multipass cell (MPC) design method based on differential evolution (DE) algorithm, and realize intelligent optimization design of MPC with small volume and long optical path. MPC is the core component of the TDLAS system. The optical path of MPC determines the detection accuracy of the TDLAS system. The optical path is affected by the position and angle of incident laser, mirror spacing, and other parameters. The DE algorithm is used to optimize the parameters that affect the performance of MPC, and a compact MPC with a spherical mirror diameter of 25.4 mm, a laser reflection number of 183, an optical path of 5.98 m, and a mirror spacing of 31.7 mm is designed. Under the same spherical mirror condition, the detection limit of MPC designed based on the DE algorithm is increased from 0.91 to 0.76 ppm compared with the MPC commonly used seven-ring spot pattern. This has a guiding and exemplary role in the design and development of high space utilization MPC.

关键词： differential evolution algorithm intelligent optimization multipass cell space utilization rate TDLAS system

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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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Finite-time sliding mode synchronisation of a fractional-order hyperchaotic system optimised using a differential evolution algorithm with dual neural networks

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IET NETWORKS 2023年第3期12卷 87-97页

作者： Shao, Keyong Feng, Ao Wang, Tingting Li, Wenju Jiang, Jilu Northeast Petr Univ Sch Elect Informat & Engn Daqing Peoples R China

To solve the synchronisation problem associated with fractional-order hyperchaotic systems, in this study, a new dual-neural network finite-time sliding mode control method was developed, and a differential evolution algorithm was used to optimise the switching gain, control parameters, and sliding mode surface parameters, greatly reducing chattering problems in sliding mode controllers. By using the developed method, the complete synchronisation of the drive system and the response system of a fractional-order hyperchaotic system was realised in a finite time;moreover, the stability of the error system under this method was proved by using Lyapunov stability theorem. Numerical simulation results verified the feasibility and superiority of the method.

关键词： differential evolution algorithm finite-time sliding mode controller fractional hyperchaotic system radial basis function neural network (RBFNN) recurrent neural network (RNN)

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Generating Black-box Audio Adversarial CAPTCHAs based on differential evolution algorithm 27

Generating Black-box Audio Adversarial CAPTCHAs based on Dif...

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27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

作者： Liu, Xinhao Yang, Hao Yan, Qiao Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Peoples R China

ISBN: (纸本)9798350349184;9798350349191

Audio adversarial CAPTCHAs are commonly used on various websites and applications to distinguish human users from automated programs. However, recent advances in deep learning have given rise to several audio recognition methods that pose a challenge to the security of audio CAPTCHAs. In this paper, we propose DE ES, a novel approach based on the differential evolution algorithm, for generating audio adversarial CAPTCHAs. Our method utilizes a momentum probability update technique to add random noise to the examples and combines differential evolution with gradient estimation to enhance the success rate of attacks. We evaluate the similarity between the adversarial examples and the original examples using audio data visualization techniques. Moreover, we apply our method to generate adversarial CAPTCHAs for two usage scenarios of audio CAPTCHAs: input-based and selection-based, respectively, to demonstrate the feasibility of the proposed algorithm. Our experimental results demonstrate that DE ES outperforms other heuristic-based generation methods in terms of the success rate of generating audio adversarial examples, while maintaining a lower average editing distance. Thus, our method provides an effective solution for generating robust audio adversarial CAPTCHAs that can, to a certain extent, withstand the attacks of deep learning models, thereby improving the security of voice-based authentication systems.

关键词： deep learning adversarial examples CAPTCHA differential evolution algorithm

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A limited-memory BFGS-based differential evolution algorithm for optimal control of nonlinear systems with mixed control variables and probability constraints

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NUMERICAL algorithmS 2023年第2期93卷 493-542页

作者： Wu, Xiang Zhang, Kanjian Guizhou Normal Univ Sch Math Sci Guiyang 550001 Peoples R China Southeast Univ Sch Elect Engn Nanjing 210096 Peoples R China Southeast Univ Sch Automat Nanjing 210096 Peoples R China Southeast Univ Key Lab Measurement & Control CSE Minist Educ Nanjing 210096 Peoples R China

In this paper, we consider an optimal control problem of nonlinear systems with mixed control variables and probability constraints. To obtain a numerical solution of this optimal control problem, our target is to formulate this problem as a constrained nonlinear parameter optimization problem (CNPOP), which can be solved by using any gradient-based numerical computation method. Firstly, some binary functions are introduced for each value of the discrete-valued control variable (DCV). Following that, we relax these binary functions and impose a penalty term on the relaxation such that the solution of the resulting relaxed problem (RP) can converge to the solution of the original problem as the penalty parameter increases. Secondly, we introduce a simple initial transformation for the probability constraints. Following that, an adaptive sample approximation method (ASAM) and a novel smooth approximation technique (NSAT) are adopted to formulate the probability constraints as some deterministic constraints. Thirdly, a control parameterization approach (CPA) is used to transform the deterministic problem (i.e., an infinite dimensional problem) into a finite dimensional CNPOP. Fourthly, in order to combine the advantages of limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithms and differential evolution (DE) algorithms, a L-BFGS-based DE (L-BFGS-DE) algorithm is proposed for solving the resulting approximation problem based on an improvied L-BFGS (IL-BFGS) method and an improved DE (IDE) algorithm. Following that, we establish the convergence result of the L-BFGS-DE algorithm. The L-BFGS-DE algorithm consists of two stages. The objectives of the first and second stages are to obtain a probable position of the global solution and to accelerate the convergence rate, respectively. In the IL-BFGS method, we propose a novel updating rule (NUR), which uses not only the gradient information of the objective function but also the value of the objective function. T

关键词： Optimal control Nonlinear systems Mixed control variables Probability constraints Limited memory BFGS method differential evolution algorithm

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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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Flow Control in Network Media Information Transmission Based on differential evolution algorithm

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WIRELESS PERSONAL COMMUNICATIONS 2022年第2期127卷 1265-1282页

作者： Liu, Libin Sun, Zhiyuan Shaanxi Radio & Televis Univ Sch Publ Adm Xian 710068 Peoples R China Xian Univ Architecture & Technol Sch Management Xian 710055 Peoples R China

In order to solve the problems of transmission delay and data loss caused by network congestion and strengthen the quality of service of transmission delay and throughput, a method of flow control in network media information transmission based on differential evolution algorithm was presented. By analyzing the delay effect of buffer on network instability, the problems of flow control at the receiving end were clarified. Moreover, the jitter between packet and end-to-end time delay parameters in dynamic caching mechanism were analyzed. The maximum and minimum values were set to calculate the balance point of real-time communication and smooth network information transmission flow. In addition, the differential evolution algorithm based on adaptive quadratic mutation of population fitness variance was used to improve the adaptive global optimization structure, organize the minimum evolution and input the minimum sample. Through reasonable selection of controller parameters and adaptive calculation, the poles of the closed-loop control system were obtained. Finally, the transmission performance index could be optimized. Thus, the stable control of transmission flow was completed. Simulation results show that the proposed algorithm can effectively improve the transmission performance of heterogeneous networks. Meanwhile, it has obvious advantages when the asymmetric parameters are high.

关键词： differential evolution algorithm Flow control Transmission delay Short-wave data

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Automatic Model for Postpartum Depression Identification using Deep Reinforcement Learning and differential evolution algorithm

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2023年第11期14卷 154-166页

作者： Shen, Sunyuan Qi, Sheng Luo, Hongfei Zhejiang Business Coll Dept Appl Engn Hangzhou 310053 Peoples R China Zhejiang Business Coll Inst Elect Commerce Hangzhou 310053 Peoples R China

Postpartum depression (PPD) affects approximately 12% of new mothers, posing a significant health concern for both the mother and child. However, many women with PPD do not receive proper care. Preventative interventions are more cost-effective for high-risk women, but identifying those at risk can be challenging. To address this problem, we present an automatic model for PPD using a deep reinforcement learning approach and a differential evolution (DE) algorithm for weight initialization. DE is known for its ability to search for global optima in high-dimensional spaces, making it a promising approach for weight initialization. The policy of the model is based on an artificial neural network (ANN), treating the categorization issue as a policymaking stage-by-stage process. The DE algorithm is used to acquire initial weight values, with the agent obtaining samples and performing classifications in each step. The habitat provides an award for every categorization activity, considering a greater award for identification of the minor category to encourage precise detection. By using a particular compensatory technique and an encouraging learning system, the operator eventually decides the most excellent method for achieving its goals. The model's efficiency is evaluated by analyzing a set of data acquired from the population-based BASIC study carried out in Uppsala, Sweden, which covers the period from 2009 to 2018 and consists of 4313 samples. The experiential results, identified by known analysis criteria, indicate that the sample achieved better precision and correctness, making it suitable for identifying PPD. The proposed model could have significant implications for identifying at-risk women and providing timely interventions to improve maternal and child health outcomes.

关键词： Postpartum depression deep reinforcement learning differential evolution algorithm weight initialization artificial neural network

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