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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Ensemble Learning-Based Wine Quality Prediction Using Optimized Feature Selection and XGBoost by Sonam Tyagi, Ishwari Singh Rajput, Bhawnesh Kumar, Harendra Singh Negi

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Optimization of Railway Equipment Maintenance Plan Based on Intelligent Patrol Inspection System by MA Yunlong

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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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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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Comprehensive Performance-Oriented Multi-Objective Optimization of Hemispherical Resonator Structural Parameters by Xiaohao Liu, Xin Jin, Chaojiang Li, Yumeng Ma, Deshan Xu, Simin Guo

“…Subsequently, the NSGA-II algorithm is applied to perform multi-objective mapping of these parameters, achieving an optimized resonator with a 4.61% increase in the minimum frequency difference from interference modes and a substantial improvement in thermoelastic damping of approximately 70.41%. …”
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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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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

“…Overall, this study highlighted the potential of combining computational techniques and machine- learning models to optimize UAV airfoil designs. These findings offer valuable insights for improving the efficiency and agility of UAVs, particularly in industries such as precision agriculture, infrastructure inspection, and environmental monitoring.…”
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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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Collision-inducing method for UAV evasive maneuvers based on receding horizon optimization by Haonan Tang, Zhigong Tang, Gong Chen, Jifeng Guo

“…The obstacle potential field-based target selection algorithm was employed to identify the most appropriate target obstacle, while the induced trajectory was determined through a combination of receding horizon optimization and the hp-adaptive pseudo-spectral method. …”
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Contextual Regularization-Based Energy Optimization for Segmenting Breast Tumor in DCE-MRI by Priyadharshini Babu, Mythili Asaithambi, Sudhakar Mogappair Suriyakumar

“…An iterative gradient descent algorithm is engaged to minimize the energy-based cost function, obtaining stable convergence towards the optimal solution. …”
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Artificial Bee Colony Algorithm Based on the Division Between Exploration and Exploitation and Its Application in Esophageal Cancer Prediction by WANG Yingcong, YAN Jun, SUN Junwei, WANG Yanfeng

“…The Wilcoxon test results indicated that there was no significant difference between ABC_DEE and GABC, but ABC_DEE significantly outperformed the other algorithms. When <italic>D</italic>=20, ABC_DEE was superior to the comparison algorithms on at least 47 functions and inferior on at most 26 functions. …”
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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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Medium and short-term load forecasting based on NPMA-LSSVM algorithm in the case of unbalance and minority sample data by YANG Qiuyu, KUANG Shusen, ZHENG Xiaogang, YE Guoqi, ZHANG Zhongxin

“…Finally, the least square support vector machine (LSSVM) load forecasting model is established, and the improved mayfly algorithm with nonlinear inertia factor and polynomial variation is used to optimize the model parameters to achieve accurate load forecasts. …”
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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

“…The results show that the hybrid algorithm has demonstrated significant performance improvement compared to the independent methods in identifying optimal values. …”
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FastClothGNN: Optimizing message passing in Graph Neural Networks for accelerating real-time cloth simulation by Yang Zhang, Kailuo Yu, Xinyu Zhang

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Nanotechnology and LSTM machine learning algorithms in advanced fuel spray dynamics in CI engines with different bowl geometries by Harish Venu, Manzoore Elahi M. Soudagar, Tiong Sieh Kiong, N. M. Razali, Hua-Rong Wei, Armin Rajabi, V. Dhana Raju, T. M. Yunus Khan, Naif Almakayeel, Erdem Cuce, Huseyin Seker

“…Abstract This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. …”
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