Optimal Coordination of Last Trains for Maximum Transfer Accessibility with Heterogeneous Walking Time by Yao Chen, Baohua Mao, Yun Bai, Tin Kin Ho, Zhujun Li

“…A discrete approximation method is proposed to reformulate the nonlinear model. The embedded Branch & Cut algorithm of CPLEX is applied to solve the models. …”
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Color Dominance-Based Polynomial Optimization Segmentation for Identifying Tomato Leaves and Fruits by Juan Pablo Guerra Ibarra, Francisco Javier Cuevas de la Rosa, Alicia Linares Ramirez

“…Similarly, a UNetmodel is used for semantic segmentation, the results of which are inferior to those obtained by the proposed interpolation optimization method. The most significant contribution of the interpolation method is that it requires only a single iteration to generate the initial data, in contrast to the iterative search required by the greedy algorithm and the lengthy training process and video card dependency of the UNet model. …”
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Product Image Generation Method Based on Morphological Optimization and Image Style Transfer by Aimin Zhou, Xinle Wang, Yujin Huang, Weitang Wang, Shutao Zhang, Jinyan Ouyang

“…The genetic algorithm is employed to build a product morphological optimization design system, obtaining product form schemes with higher esthetic quality. …”
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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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Identifying the Combined Impacts of Sensor Quantity and Location Distribution on Source Inversion Optimization by Shushuai Mao, Jianlei Lang, Feng Hu, Xiaoqi Wang, Kai Wang, Guiqin Zhang, Feiyong Chen, Tian Chen, Shuiyuan Cheng

“…Sensor number and location distribution both play important roles in source inversion; however, their combined impacts on source inversion optimization remain poorly understood. In our study, the optimization inversion method is established based on the Gaussian plume model and the generation algorithm. …”
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Design and Multiobjective Optimization of Magnetorheological Damper considering the Consistency of Magnetic Flux Density by Zhizhen Dong, Zhimin Feng, Yuehua Chen, Kefan Yu, Gang Zhang

“…Then, the multiobjective optimization function and the working flow of optimal design are presented by combining the parallel-plate model of the MR damper with the function posed before. …”
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Gorilla troops optimization with deep learning based crop recommendation and yield prediction by A. Punitha, V. Geetha

“…This article introduces a Gorilla Troops Optimization with Deep Learning-based Crop Recommendation and Yield Prediction model (GTODL-CRYPM). …”
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Software development of tooth profile parameter optimization and meshing characteristic analysis of flexspline by FAN Zhengwu, LIU Yujie, ZHANG Ruiliang

“…ObjectiveIn order to improve the meshing performance and design efficiency of harmonic gears, a tooth profile optimization method aiming at increasing the meshing conjugate interval was proposed, and the design and analysis software was developed.MethodsFirstly, based on the basic principle of harmonic gear transmission, the mathematical model of theoretical conjugate region and conjugate tooth profile was established, and the tooth profile of the rigid gear was obtained. …”
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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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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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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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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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Expansion of Output Spatial Extent in the Wavenumber Domain Algorithms for Near-Field 3-D MIMO Radar Imaging by Yifan Gong, Limin Zhai, Yan Jia, Yongqing Liu, Xiangkun Zhang

“…To suppress aliasing while expanding the output spatial extent, an optimization approach for the wavenumber domain algorithms is proposed. …”
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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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Study on the Evolutionary Characteristics of Spatial and Temporal Patterns and Decoupling Effect of Urban Carbon Emissions in the Yangtze River Delta Region Based on Neural Network... by Xichun Luo, Chaoming Cai, Honghao Zhao

“…To improve the performance of neural network models, the Aquila Optimizer (AO) algorithm is introduced to optimize the hyper-parameter values in the back-propagation (BP) neural network model in this research due to the appealing searching capability of AO over traditional algorithms. …”
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Optimizing Robotic Arm Learning: Curiosity-Driven Deep Deterministic Policy Gradient by Liu Jiarun

“…However, collecting the large- scale real-world data is costly and impractical, making simulation environments essential for optimization. …”
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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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Hybrid Gradient Descent Grey Wolf Optimizer for Machine Learning Performance Enhancement by Sri Rossa Aisyah Puteri Baharie, Sugiyarto Surono, Aris Thobirin

“…Advancements in machine learning have enabled the development of more accurate and efficient health prediction models. This study aims to improve diabetes prediction performance using the Support Vector Machine (SVM) model optimized with the Hybrid Gradient Descent Gray Wolf Optimizer (HGD-GWO) method. …”
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Parking Demand Prediction Method of Urban Commercial-Office Complex Buildings Based on the MRA-BAS-BP Algorithm by Xiang Tang, Jianxiao Ma, Shun Zhou, Tianci Shan

“…In this paper, a two-level and ten-category index system is established and then mixed with the BP algorithm through the MRA model to improve the overall robustness and accuracy of the algorithm. …”
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