Multitask Level-Based Learning Swarm Optimizer by Jiangtao Chen, Zijia Wang, Zheng Kou

“…Although many evolutionary multitask algorithms (EMTAs) based on traditional differential evolution (DE) and the genetic algorithm (GA) have been proposed, there are relatively few EMTAs based on particle swarm optimization (PSO). …”
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A Quasiphysics Intelligent Model for a Long Range Fast Tool Servo by Qiang Liu, Xiaoqin Zhou, Jieqiong Lin, Pengzi Xu, Zhiwei Zhu

“…To identify the parameters of the LPM, a novel Opposition-based Self-adaptive Replacement Differential Evolution (OSaRDE) algorithm is proposed which has been proved to have a faster convergence mechanism without compromising with the quality of solution and outperform than similar evolution algorithms taken for consideration. …”
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A multi-strategy improved snake optimizer and its application to SVM parameter selection by Hong Lu, Hongxiang Zhan, Tinghua Wang

“…The novel evolutionary population dynamics model (NEPD) was beneficial for searching accurately. The differential evolution strategy (DES) helped to reduce the probability of falling into local optimal value. …”
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A hybrid model combining environmental analysis and machine learning for predicting AI education quality by Xinyu Ren

“…Also, in order to evaluate the quality of AI training programs in higher education, a new approach based on the multilayer perceptron (MLP) algorithm was presented in which the capuchin search algorithm (CapSA) was used to adjust the weight vector of the neural network. …”
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On modeling approaches for the predictive simulation of living systms dymamics by Ivan Mura

“…REVISTA DE INVESTIGACIÓN DE LA FACULTAD DE INGENIERÍA This research paper describes two main approaches that are currently available for modelling and simulating the evolution of dynamic living systems, namely the continuous-deterministic one, which is rendered by systems of ordinary differential equations and the discrete-stochastic one, which bases on the Stochastic simulation algorithm proposed by Gil/espíe in 1976. …”
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Experimental Verification of Optimized Multiscroll Chaotic Oscillators Based on Irregular Saturated Functions by J. M. Muñoz-Pacheco, D. K. Guevara-Flores, O. G. Félix-Beltrán, E. Tlelo-Cuautle, J. E. Barradas-Guevara, C. K. Volos

“…Then, the positive Lyapunov exponent is optimized using the differential evolution algorithm to obtain chaotic attractors with 2 to 5 scrolls. …”
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Primitive-Level vs. Implementation-Level DPA Security: a Certified Case Study by Charles Momin, François-Xavier Standaert, Corentin Verhamme

“… Implementation-level countermeasures like masking can be applied to any cryptographic algorithm in order to mitigate Differential Power Analysis (DPA). …”
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Robotic Tack Welding Path and Trajectory Optimization Using an LF-IWOA by Bingqi Jia, Haihong Pan, Lei Zhang, Yifan Yang, Huaxin Chen, Lin Chen

“…To overcome these challenges, a Lévy flight-enhanced improved whale optimization algorithm (LF-IWOA) was developed. The algorithm combines elite opposition-based learning (EOBL), differential evolution (DE), and Lévy flight (LF) to improve global exploration capability, increase population diversity, and improve convergence. …”
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Automated Detection of Central Retinal Artery Occlusion Using OCT Imaging via Explainable Deep Learning by Ansgar Beuse, Daniel Alexander Wenzel, MD, Martin Stephan Spitzer, MD, Karl Ulrich Bartz-Schmidt, MD, Maximilian Schultheiss, MD, Sven Poli, MD, Carsten Grohmann, PhD, MD

“…Our model followed a multiclass approach, distinguishing among the 3 different classes: control, CRAO, and differential diagnoses. …”
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Enhancing security and efficiency in Mobile Ad Hoc Networks using a hybrid deep learning model for flooding attack detection by Pramodh Krishna D., E. Sandhya, Khaja Shareef Sk, Srihari Varma Mantena, Venkata Subbaiah Desanamukula, Ch Koteswararao, Srinivasa Rao Vemula, Maruthi Vemula

“…To optimize the model’s efficiency, a unique DECEHGS algorithm combining Differential Evolution and Evolutionary Population Dynamics techniques is employed, enhancing both convergence and performance. …”
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Harmonic oscillator based particle swarm optimization. by Yury Chernyak, Ijaz Ahamed Mohammad, Nikolas Masnicak, Matej Pivoluska, Martin Plesch

“…This physics-based approach allows smoother convergence throughout the optimization process and wider tunability options. We evaluated our method on a standard set of test functions and demonstrated that, in most cases, it outperforms its natural competitors, including the original PSO, as well as commonly used optimization methods such as COBYLA and Differential Evolution.…”
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Coevolution of Artificial Agents Using Evolutionary Computation in Bargaining Game by Sangwook Lee

“…We present three kinds of EC based agents (EC-agent) participating in the bargaining game: genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE). …”
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DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion. by Xicheng Sun, Fu Lv, Yongan Feng, Xu Zhang

“…The experimental results demonstrate that the proposed method outperforms other algorithms in both subjective and objective evaluation results. …”
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Task Allocation and Saturation Attack Approach for Unmanned Underwater Vehicles by Qiangqiang Chen, Baisheng Liu, Changdong Yu, Mingkai Yang, Haonan Guo

“…In the task allocation link, the grey wolf optimizer is improved by introducing Logistic chaos mapping and differential evolution mechanism, which improves the search efficiency and allocation accuracy. …”
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Optimization of Hybrid Laminates with Extension-Shear Coupling by Da Cui, Daokui Li

“…The extension-shear-coupled effect of hybrid laminates is optimized with improved differential evolution algorithm. Results are presented for the hybrid laminates that consist of carbon fiber and glass fiber composite materials. …”
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Cooperative spectrum sensing scheme against SSDF attack based on ESD test in radio network by Lichun XIE, Chunqin ZHANG

“…Aiming at the problem that the cooperative spectrum sensing vulnerable to falsify data attacks in cognitive radio network, a cooperative spectrum sensing scheme with against SSDF attack based on test statistic and extreme studentized deviate test was proposed. Firstly, the differential evolution algorithm and weighted gain combining soft decision scheme were combined to form an efficient node decision fusion mechanism. …”
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基于改进Kriging模型的主动学习可靠性分析方法 by 陈哲, 杨旭锋, 程鑫

“…Active learning Kriging（ ALK） model is able to only approximate the performance function in a narrow region around the limit state surface.Therefore,the efficiency of reliability analysis is remarkably improved.However,most of the existing strategies build the ALK model based on a so-called DACE toolbox.DACE cannot obtain the global optimal parameter of a Kriging model and the training point chosen in each iteration cannot be the optimal one.In this paper,one famous global optimization,i.e.,the differential evolution algorithm is introduced to explore the optimal parameter of Kriging model and improve the accuracy of Kriging prediction information.As a result,the training point in each iteration is guaranteed to be the global optimal one and the efficiency of ALK model is largely improved.…”
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Kinematics Analysis of 3T1R 4-PRP_aU Parallel Mechanism by Shikun Wen, Linxian Che, Li Du, Guowang Chen

“…In accordance with the condition of rod length， the model of positional forward solution is established， then it is transformed into an unconstrained optimization problem and solved by differential evolution algorithm. The analytical expression of the inverse solution of mechanism position is derived and the correctness of the forward displacement of mechanism position is verified by using the inverse solution of mechanism position. …”
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A New Method Calculating Stresses and Displacements in Elastic Bars by Z. Górecki, J. Rybicki

“…The algorithm is based on Vlasov's shell theory. The differential equations derived are solved numerically by means of the method of splines. …”
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Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization by ZHONG Chuanjie, CHENG Wenming, DU Run, GAO Xuchao, ZHANG Lin

“…However, the difference was slight. Since the output of the multi-objective algorithm was a Pareto solution set, four indices, uniformity, convergence, diversity, and dominance, were selected to evaluate the distribution in the solution space and to compare the solution results of each algorithm. …”
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