An Intelligent Optimization System Using Neural Networks and Soft Computing for the FMM Etching Process by Wen-Chin Chen, An-Xuan Ngo, Jun-Fu Zhong

“…Experimental results demonstrate a marked improvement in product yield and process stability while reducing manufacturing costs. …”
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Design and optimization of distributed energy management system based on edge computing and machine learning by Nan Feng, Conglin Ran

“…Future research can further explore how to integrate multiple machine learning algorithms to optimize energy scheduling strategies and improve the system’s adaptability in complex environments.…”
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Optimizing Small Cell Performance: A New MIMO Paradigm With Distributed ASTAR-RISs by Shakil Ahmed, Ahmed E. Kamal, Mohamed Y. Selim, Md Akbar Hossain, Saifur Rahman Sabuj

“…Our proposed method uses an alternating optimization algorithm to optimize the phase shift matrix at the ASTAR-RIS and the hybrid beamforming at the mBS. …”
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Leveraging a disulfidptosis-based signature to characterize heterogeneity and optimize treatment in multiple myeloma by Bingxin Zhang, Dong Zheng, Shuxia Zhu, Xinyi Zhang, Quanqiang Wang, Zhili Lin, Ziwei Zheng, Shujuan Zhou, Zixing Chen, Sisi Zheng, Enqing Lan, Luning Cui, Hansen Ying, Yu Zhang, Xuanru Lin, Qiang Zhuang, Honglan Qian, Xudong Hu, Yan Zhuang, Qianying Zhang, Zhouxiang Jin, Songfu Jiang, Yongyong Ma, Yongyong Ma, Yongyong Ma

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A Sequential Generation Redispatch Algorithm to Ensure Power System Small Signal Stability under Low-Frequency Oscillations by Hassan Golzari-Kolur, Seyed Mohammad-Taghi Bathaee, Turaj Amraee

“…Then, in the process of improving the small signal stability, the modal analysis specifies the system stability status in each step, and the proposed second-order convex redispatch model defines the optimal direction of generation rescheduling. …”
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Multi-Objective Optimization of Machinability and Energy Consumption of Cast Iron Depending on Cooling Rate by Burak Öztürk, Fuat Kara

“…Energy efficiency has become a critical focus in sustainable production techniques and cost-effective machining processes. This variation directly influences machinability, with higher hardness generally improving surface quality. …”
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Optimal design and performance prediction of stepped honeycomb labyrinth seal using CFD and ANN by Geunseo Park, Min Seok Hur, Tong Seop Kim

“…An ANN-based performance prediction metamodel was developed, and a genetic algorithm was applied to the metamodel to optimize seal geometry, achieving a 12.34% improvement in leakage performance over the reference seal. …”
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Application of adaptive virtual synchronous generator based on improved active power loop in photovoltaic storage systems by Youzhuo Zheng, Yutao Xu, Yekui Yang, Long Hua, Yuqing Yang

“…Then, the adaptive inertia algorithm is incorporated into the active power loop of the VSG control, and an adaptive inertia control method based on the improved active power loop is proposed. …”
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Implementation of personalized customization and enhanced experiences for cultural tourism resources using genetic algorithm-based virtual reality technology by Huiya Xing, Xiangyi Li, Min Liu, Yicong Zhong

“…By adjusting to these individual parameters, the algorithm cleverly optimizes tourist itineraries. The DDE-GA-powered VR system works better than current methods, according to experimental data, with improvements in reaction time (1.1 s), accuracy (98 %), precision (97 %), and modeling error (0.10). …”
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Diverse solitons wave structures for coupled NLSEs in birefringent fibers with higher nonlinearities using the modified extended mapping algorithm by Karim K. Ahmed, Njah A. Alsahafi, Hamdy M. Ahmed, Salah Boulaaras, M. S. Osman

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Comparison of Support Vector Machine and Decision Tree Algorithm Performance with Undersampling Approach in Predicting Heart Disease Based on Lifestyle by Gusti Ayu Putu Febriyanti, Anna Baita

“…The K-fold cross-validation method with K=10 and hyperparameter tuning were applied to obtain the optimal performance of both models. The results showed that SVM without undersampling achieved 92% accuracy, while with undersampling the accuracy decreased to 76%. …”
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Flaw-YOLOv5s: A Lightweight Potato Surface Defect Detection Algorithm Based on Multi-Scale Feature Fusion by Haitao Wu, Ranhui Zhu, Hengren Wang, Xiangyou Wang, Jie Huang, Shuwei Liu

“…To elevate detection accuracy as well as shorten the computational load of the model, this paper proposes a lightweight Flaw-YOLOv5s algorithm for potato surface defect detection. …”
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Classification of Anxiety Levels of IGD Patients at RSU Royal Prima Medan Using Support Vector Machine (SVM) Algorithm by Kharisma Gunanta Ginting, Nugroho Prasetyo, Al Vino Gunawan, Magdalena Sihombing, Adli Abdillah Nababan

“…The preprocessing process includes imputing missing values and normalizing numerical features so that the model can learn optimally. Performance evaluation shows that the use of SMOTE increases classification accuracy from 95% to 97%, as well as improving precision, recall, and F1-score metrics at almost all anxiety levels. …”
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Adversarial Reinforcement Learning-Based Converged Communication Efficiency Improvement Method for Power Distribution Network by Linyu PENG, Xu LIU, Wei TANG, Qing LIU, Hao FANG, Guanghui ZHANG

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Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction by Qian Zeng, Xiaobo Li, Yixuan Chen, Minghao Yang, Xingbang Liu, Yuetian Liu, Shiwei Xiu

“…To validate the effectiveness of the proposed methods, we conduct multiple controlled experiments focusing on both location prediction models and service allocation algorithms. The results show that, compared to the baseline methods, our approach achieves improvements of 2.56%, 5.29%, and 2.16% in terms of the average user connection to edge servers, average service deployment cost, and average service allocation execution time, respectively, demonstrating the superiority and feasibility of the proposed methods.…”
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BIT*+TD3 Hybrid Algorithm for Energy-Efficient Path Planning of Unmanned Surface Vehicles in Complex Inland Waterways by Yunze Xie, Yiping Ma, Yiming Cheng, Zhiqian Li, Xiaoyu Liu

“…To address the limitations of traditional path planning algorithms in dynamic environments, the proposed BIT*+TD3 model leverages the BIT* algorithm to generate initial paths in static environments through elliptical informed sampling and heuristic search. …”
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Innovative IoT-enabled mask detection system: A hybrid deep learning approach for public health applications by Parul Dubey, Vinay Keswani, Pushkar Dubey, Gunjan Keswani, Dhananjay Bhagat

“…The novelty of the paper lies in combining AFSO with a hybrid deep learning architecture for parameter optimization and improved scalability. Performance metrics such as accuracy, sensitivity, precision, and F1-score were used to evaluate the model. …”
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Autonomous Maneuver Decision of UCAV Air Combat Based on Double Deep Q Network Algorithm and Stochastic Game Theory by Yuan Cao, Ying-Xin Kou, Zhan-Wu Li, An Xu

“…Then, the double deep Q network (DDQN) algorithm in reinforcement learning (RL) is introduced to train the agent by the interaction with the environment and combined with Minimax algorithm in stochastic game theory to solve the optimal value function in each specific state, and the optimal maneuver decision of UCAV is obtained. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…This study presents a comparative analysis of hyper-parameter optimization methods used in developing predictive models for patients at risk of heart failure readmission and mortality. …”
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Reliability evaluation and multi-objective optimization of combustion chamber’s key components of marine engine by Lei Hu, Wentong Wang, Xu Wang, Jianguo Yang, Yonghua Yu, Chunyang Mei

“…Constrained multi-objective optimization of reliability is conducted through contrastive analysis of different optimization algorithms. …”
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