Design by Optimization on the Nozzle and the Stator Blades of a Rim-Driven Pumpjet by Marco Lugaresi, Diego Villa, Stefano Gaggero

“…The design of the stator and nozzle of a rim-driven pumpjet thruster (RDPJ) is addressed through a simulation-based design optimization approach built on a parametric description of the main geometrical characteristics of the system, a RANS solver with actuator disk model, and a genetic algorithm. …”
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The Effect of Entropy on the Performance of Modified Genetic Algorithm Using Earthquake and Wind Time Series by Manuel Vargas, Guillermo Fuertes, Miguel Alfaro, Gustavo Gatica, Sebastian Gutierrez, María Peralta

“…The dynamic complexity of time series of natural phenomena allowed to improve the performance of the genetic algorithm to optimize the test mathematical functions. …”
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An Igneous Rock Lithology Identification Method Based on Data-Algorithm Bidirectional-Driven Framework by HAN Ruiyi, SONG Xiaoni, WANG Xinru, GUO Yuhang

“…First, a feature space optimization algorithm constrained by discrete minerals is developed, integrating mineral chemical components with log data to establish a petrophysically meaningful feature characterization framework. …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…The findings indicate that the RF and SVM algorithms outperform other models in predicting operational risk across all scenarios. …”
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Development of a postoperative recurrence prediction model for stage Ⅰ non-small cell lung cancer patients using multimodal data based on machine learning by ZHANG Di, WU Yi, XU Yu

“…A combined model was further constructed by integrating both feature sets, and model performance was compared to identify the optimal predictive model.Results‍　‍This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model. …”
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An Experimental Comparison of Self-Adaptive Differential Evolution Algorithms to Induce Oblique Decision Trees by Rafael Rivera-López, Efrén Mezura-Montes, Juana Canul-Reich, Marco-Antonio Cruz-Chávez

“…This study addresses the challenge of generating accurate and compact oblique decision trees using self-adaptive differential evolution algorithms. Although traditional decision tree induction methods create explainable models, they often fail to achieve optimal classification accuracy. …”
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Design of performance evaluation method for higher education reform based on adaptive fuzzy algorithm by Dakun Yang, Muhammad Sheraz Arshad Malik

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Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis Dynamometer by Xiaorui Zhang, Xingyuan Xu, Hengliang Shi

“…The test results indicate that the testing error of the optimized algorithm for the loading model decreases from 6.4% to 1.8%. …”
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CF-YOLO for small target detection in drone imagery based on YOLOv11 algorithm by Chengcheng Wang, Yuqi Han, Chenggui Yang, Mingjie Wu, Zaiqing Chen, Lijun Yun, Xuesong Jin

“…Experiments show that on the public VisDrone dataset, TinyPerson dataset, and HIT-UAV dataset, CF-YOLO improves the mAP50 by 12.7%, 10.1%, and 3.5%, respectively, compared to the baseline model. …”
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On the implementation of a global optimization method for mixed-variable problems by Nannicini, Giacomo

“…We propose several modifications aimed at generalizing and improving these two algorithms: (i) the use of an extended space to represent categorical variables in unary encoding; (ii) a refinement phase to locally improve a candidate solution; (iii) interpolation models without the unisolvence condition, to both help deal with categorical variables, and initiate the optimization before a uniquely determined model is possible; (iv) a master-worker framework to allow asynchronous objective function evaluations in parallel. …”
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Flexible Adaptive Marine Predator Algorithm and Its Application in Fault Detection for Wind Turbines by WANG Wen, YI Jiabiao

“…FAMPA allows for flexibly adjusting population location changes to optimize the balance between global exploration and local exploitation, thus significantly improving both convergence rates and optimization accuracy. …”
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Offshore Optical-wireless Integrated Access Network Deployment Algorithm based on MHA-MAD by LI Xuehua, XI Tong, WANG Xin, HUANG Xiang

“…【Methods】This study proposes a Multi-Head Attention enhanced Multi-Agent Deep Q-Network (MHA-MAD) algorithm. It efficiently extracts key features of the network environment using multi-head attention mechanism and assigns dynamic weights to different features, thereby improving modeling accuracy. …”
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Risk of AI Algorithmic Discrimination Embedded in Government Data Governance and Its Prevention and Control by PENG Lihui, ZHANG Qiong, LI Tianyi

“…To address this issue, this study proposed a series of targeted prevention and control measures, including clarifying the principle of algorithmic fairness, formulating industry norms and standards, improving the accountability mechanism and regulatory system, and optimizing the data collection and processing environment, so as to effectively curb the phenomenon of algorithmic discrimination while making full use of the advantages of AI technology, so that AI technology in government data governance can truly benefit the people, and promote social fairness and justice.…”
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Enhancing adaptive beamforming by enhanced MUSIC algorithm for urban environments in O-RAN architecture by Mustafa Mayyahi, Jordi Mongay Batalla, Constandinos X. Mavromoustakis

“…By leveraging the accuracy of the multiple signal classification (MUSIC) algorithm combined with predictive linear regression (LR) and support vector regression (SVR) models, our approach significantly enhances the MUSIC algorithm and accelerates the generation of beam weights for the beamforming system. …”
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A Hybrid Particle Swarm Optimizer for Curriculum Sequencing Problem by Xianjie Peng, Xiaonan Sun, Zhen He

“…Second, an adaptive polynomial mutation is introduced in PSO to further improve its diversity preservation ability. Furthermore, a curriculum scheduling model is proposed, where several constraints are taken into considerations to ensure the practicability of the curriculum sequencing. …”
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Machine Learning Techniques for Heart Disease Prediction Using a Multi-Algorithm Approach by Muhammad Kunta Biddinika, Alya Masitha, Herman Herman, Vita Arfiana Nurul Fatimah

“…The novelty of this study lies in the comparative analysis of several algorithms to optimize the heart disease prediction model for clinical use. …”
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Data Enabled Predictive Control for Water Distribution Systems Optimization by Gal Perelman, Avi Ostfeld

“…Abstract Recent developments in control theory, coupled with the growing availability of real‐time data, have paved the way for improved data‐driven control methodologies. This study explores the application of the Data‐Enabled Predictive Control (DeePC) algorithm to optimize the operation of water distribution systems (WDS). …”
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Optimized Dynamic Deployment of UAVs in Maritime Networks with Route Prediction by Yanli Xu, Yalan Shi

“…The PPO algorithm can optimize the deployment strategy in dynamic environments, improve communication coverage, and reduce energy consumption. …”
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Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…This study integrated hyperspectral technology with machine learning algorithms to model complex nonlinear relationships and to select the optimal SWHC model. …”
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Robot Task-Constrained Optimization and Adaptation with Probabilistic Movement Primitives by Guanwen Ding, Xizhe Zang, Xuehe Zhang, Changle Li, Yanhe Zhu, Jie Zhao

“…We separate ProMPs as Gaussians at each timestep and minimize Kullback–Leibler (KL) divergence, with a gradient ascent–descent algorithm performed to obtain optimized ProMPs. Given optimized ProMPs, we outline a unified robot movement adaptation method for extending from a single obstacle to multiple obstacles. …”
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