Optimal strategy selection method for moving target defense based on signaling game by Lyu JIANG, Hengwei ZHANG, Jindong WANG

“…To solve the problem of the optimal strategy selection for moving target defense,the defense strategy was defined formally,the defense principle from the perspective of attack surface shifting and exploration surface enlarging was taken into account.Then,network attack-defense behaviors were analyzed from the sight of dynamic confrontation and bounded information.According to the analysis of attack-defense game types and confrontation process,the moving target defense model based on signaling game was constructed.Meanwhile,the method to quantify strategies was improved and the solution of perfect Bayesian equilibrium was proposed.Furthermore,the optimal defense strategy selection algorithm was designed by the equilibrium analysis.Finally,the simulation demonstrates the effectiveness and feasibility of the proposed optimal strategy and selection method.…”
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Research on Optimization of Large-Scale Heterogeneous Combat Network Based on Graph Embedding by Xianzheng Meng, Changrong Xie, Hui Li, Guangjun Zeng, Kebin Chen

“…It has shown a 17.23% improvement in this aspect compared to HCNOF0 and a 6.89% enhancement when compared to the GE-SU-EANet algorithm, underscoring its advantages in both optimization performance and cost reduction. …”
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Control optimization for permanent magnet synchronous generators in multi-source power systems by LI Lingyun, LIU Weizhi, WANG Yongxiang, LIU Yang

“…A novel approach was proposed that incorporates a Lagrangian function based on the principles of maximum torque and minimum loss to solve for the direct-axis and quadrature-axis currents, leading to the creation of a voltage stability control strategy that integrates vector control with efficiency optimization control. On this basis, a fuzzy fractional-order super-twisting sliding mode control algorithm was introduced to improve the flexibility and performance of the established control strategy. …”
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Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization by Sumet Mehta, Fei Han, Muhammad Sohail, Bhekisipho Twala, Asad Ullah, Fasee Ullah, Arfat Ahmad Khan, Qinghua Ling

“…The analysis of high-dimensional microarray gene expression data presents critical challenges, including excessive dimensionality, increased computational burden, and sensitivity to random initialization. Traditional optimization algorithms often produce inconsistent and suboptimal results, while failing to preserve local data structures limiting both predictive accuracy and biological interpretability. …”
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An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things by Mai Alduailij

“…To further optimize model performance, the pelican optimization algorithm (POA) is utilized for hyperparameter tuning to ensure that the optimum hyperparameters are chosen for enhanced accuracy. …”
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Hyperparameter Optimization for Tomato Leaf Disease Recognition Based on YOLOv11m by Yong-Suk Lee, Maheshkumar Prakash Patil, Jeong Gyu Kim, Yong Bae Seo, Dong-Hyun Ahn, Gun-Do Kim

“…This model underwent rigorous hyperparameter optimization using the one-factor-at-a-time (OFAT) algorithm, with a focus on essential parameters such as batch size, learning rate, optimizer, weight decay, momentum, dropout, and epochs. …”
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Discrete Optimization on Truck-Drone Collaborative Transportation System for Delivering Medical Resources by Min Lin, Yuming Chen, Rui Han, Yao Chen

“…In this system, delivery tasks are assigned to multiple trucks and multiple drones on each truck can perform delivery tasks in parallel, thereby improving delivery efficiency. We study the routing problem of this system specifically for medical supplying road network and establish mixed-integer model and hybrid algorithm. …”
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Optimal Design and Dynamic Performance Analysis of Vehicle Suspension Employing an Eccentric Inerter by Chengqun Qiu, Ang Chen, Yuqiu Xu, Yujie Shen

“…Then, by considering the overall performance such as the vehicle body acceleration, the suspension working space, and the dynamic tire load, the key parameters of the two suspensions are optimized by using the genetic algorithm. Simulation analysis results indicate that the series-connected vehicle ISD suspension is superior to the parallel-connected one, and all of the RMS values of the body acceleration, the suspension working space, and the dynamic tire load are decreased significantly by comparing to the conventional suspension, while the improvement of the parallel-connected vehicle ISD suspension is relatively poor. …”
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Optimization design of structural parameters of fan diaphragm coupling under the high torque by SUN Jiaxin, CAI Anwen, HU Weihui, DU Jing, SUN Weiwei, QIN Zhongzheng

“…ObjectiveThe existing research on diaphragm couplings mainly focuses on the mechanical performance of different types of diaphragm couplings and the optimization of diaphragm size and shape through various optimization algorithms. …”
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Optimizing mRNA Vaccine Degradation Prediction via Penalized Dropout Approaches by Hwai Ing Soon, Azian Azamimi Abdullah, Hiromitsu Nishizaki, Latifah Munirah Kamarudin

“…A novel tetramer-label encoding approach (4-mer-lbA) was proposed, integrating biological relevance with data-driven analysis to enhance predictive accuracy. To further optimize model performance, two advanced hyperparameter optimization (HPO) techniques—Dropout-Enhanced Technique (DEet) and Hyperparameter Optimization Algorithm Penalizer (HOPeR)—are proposed to mitigate overfitting, address inefficiencies in conventional HPO algorithms (HPOAs), and accelerate model convergence. …”
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Aerodynamic analysis and ANN-based optimization of NACA airfoils for enhanced UAV performance by Sanan H. Khan, Mohd Danish, Md. Ayaz, Afsar Husain, Shamma Saeed, Shamma Abdulla, Shama Shaheen, Alia Saeed, Ahmed Thaher

“…This study analyzed three National Advisory Committee for Aeronautics (NACA) airfoil profiles: NACA 2412, NACA 4415, and NACA 0012, using a combination of computational fluid dynamics (CFD), XFOIL simulations, and a hybrid artificial neural network-genetic algorithm (ANN-GA) model. This study aimed to evaluate and optimize the aerodynamic performance of these airfoils under various flight conditions. …”
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Research on Motion Transfer Method from Human Arm to Bionic Robot Arm Based on PSO-RF Algorithm by Yuanyuan Zheng, Hanqi Zhang, Gang Zheng, Yuanjian Hong, Zhonghua Wei, Peng Sun

“…To address this shortcoming, this study presents a motion transfer method from the human arm to a bionic robot arm based on the hybrid PSO-RF (Particle Swarm Optimization-Random Forest) algorithm to improve joint space mapping accuracy and dynamic compliance. …”
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Resolving Contrast and Detail Trade-Offs in Image Processing with Multi-Objective Optimization by Daniel Molina-Pérez, Alam Gabriel Rojas-López

“…This trade-off is tackled using a multi-objective optimization approach. Specifically, the proposal’s model integrates the sigmoid transformation function and unsharp masking highboost filtering with the NSGA-II algorithm. …”
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Machine-Learning-Algorithm-Assisted Portable Miniaturized NIR Spectrometer for Rapid Evaluation of Wheat Flour Processing Applicability by Yuling Wang, Chen Zhang, Xinhua Li, Longzhu Xing, Mengchao Lv, Hongju He, Leiqing Pan, Xingqi Ou

“…By employing an improved whale optimization algorithm (iWOA) coupled with a successive projections algorithm (SPA), we selected the 20 most informative wavelengths (MIWs) from the full range spectra, allowing the iWOA/SPA-SOA-SVR model to predict SV with correlation coefficient and root-mean-square errors in prediction (R_P and RMSE_P) of 0.9605 and 0.2681 mL. …”
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Optimal Allocation of Distributed Generators in Active Distribution Network considering TOU Price by Hongbo Liu, Shencheng Liu, Xueyang Gai, Yongfa Liu, Yutong Yan, Li Sun

“…An improved simulated annealing particle swarm optimization algorithm is also proposed by refining the initialized population based on the niche fitness, introducing inertia weight with chaotic disturbance and accelerating local search with learning factor of dynamic parameter. …”
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Comparative Analysis of a Quantum SVM With an Optimized Kernel Versus Classical SVMs by Matheus Cammarosano Hidalgo

“…Businesses across industries face challenges in improving customer retention and reducing churn, making predictive models essential for identifying at-risk customers and enhancing revenue. …”
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Optimization Design and Propulsion System Sizing Methodology of Double-Layer Staggered Octocopter by He Zhu, Yuanzun Wei, Hong Nie, Xiaohui Wei, Siqiang Deng

“…An optimal structural configuration of the DLSO is then obtained by applying the adaptive geometry estimation–based multiobjective evolutionary algorithm (AGE-MOEA). …”
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A Novel Hybrid Metaheuristic MPA-PSO to Optimize the Properties of Viscous Dampers by Elmira Shemshaki, Mohammad Hasan Haddad, Mohammadreza Mashayekhi, Seyyed Meisam Aghajanzadeh, Ali Majdi, Ehsan Noroozinejad Farsangi

“…Structural modeling and dynamic analyses are performed using OpenSees 3.5.0 software, and damper parameter optimization is performed through a new combination of two marine predator algorithms (MPA) and particle swarm optimization (PSO). …”
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Towards few-shot learning with triplet metric learning and Kullback-Leibler optimization by Yukun Liu, Xiaojing Wei, Daming Shi, Dan Xiang, Junliu Zhong, Hai Su

“…In training, the deep learning and expectation-maximization algorithm are used to optimize models. Intensive experiments have been conducted on three popular benchmark datasets, and the experimental results show that this method significantly improves the classification ability of few-shot learning tasks and obtains the most advanced performance.…”
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Application of Improved WOA in Hammerstein Parameter Resolution Problems under Advanced Mathematical Theory by Lu Zhao, Jiangjun Liu, Yuan Li

“…In response to the fact that whale optimization algorithms are prone to falling into local optima and the identification of important Hammerstein models ignores the issue of noise outliers in actual industrial environments, this study improves the whale algorithm and constructs a Hammerstein model identification strategy for nonlinear systems under heavy-tailed noise using the improved whale algorithm. …”
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