Failure thresholds and weak part identification in cascade reservoir system: A risk-based optimization framework by Haibin Wang, Jiahong Liu, Chao Mei, Jia Wang, Tianxu Song

“…Secondly, a dynamic Particle Swarm Optimization-Genetic Algorithm (PSO-GA) model optimizes outflow strategies during flood events. …”
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Adaptive optimization decision system for plate-fin heat Exchangers: An integrated approach to enhancing efficiency and performance by Na Sun, Shuai Zhang, Nan Li, Zijian Li, Meng He, Zhengchun Shen, Ke Wang, Xiaoyong Guo, Wen-Quan Tao

“…The GSA module uses the Sobol method to evaluate the impact of design variables on performance. The optimization module employs the Newton-Raphson-based optimizer (NRBO) and the multi-strategy improved grey wolf optimization algorithm (MIGWO). …”
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Deceptive Cyber-Resilience in PV Grids: Digital Twin-Assisted Optimization Against Cyber-Physical Attacks by Bo Li, Xin Jin, Tingjie Ba, Tingzhe Pan, En Wang, Zhiming Gu

“…A non-dominated sorting genetic algorithm (NSGA-III) is employed to achieve Pareto-optimal solutions, ensuring high system resilience while minimizing computational burdens. …”
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Optimization of Remote Backup Protection Coordination Logic Based on Dynamic Identification of Faulty Components in Transmission Grids by LIN Xiangning, JI Jihao, DING Yifan, LI Zhengtian, WENG Hanli

“…For symmetrical faults， the traveling wave ranging error is less than 100 m， and the location time is reduced by 90% compared with traditional methods. After optimization， the remote backup-action delay was reduced from 4-7 intervals to 2 intervals， while the setting coverage increased by 18.4%， effectively avoiding misoperations owing to load intrusion. …”
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Construction of Analogy Indicator System and Machine-Learning-Based Optimization of Analogy Methods for Oilfield Development Projects by Muzhen Zhang, Zhanxiang Lei, Chengyun Yan, Baoquan Zeng, Fei Huang, Tailai Qu, Bin Wang, Li Fu

“…To meet the need for quick evaluation of overseas oilfield projects with limited data and experience, this study develops an analogy indicator system and tests multiple machine-learning algorithms on two analogy tasks to identify the optimal method. …”
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A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements by Zheng Zeng, Linkai Tao, Hangyu Zhu, Yunfeng Zhu, Long Meng, Jiahao Fan, Chen Chen, Wei Chen

“…The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. …”
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Hybrid Automata-Based Control Framework for Real-Time Optimization in Space-Based Solar Power Transmission by Patil Ankita, Ranjan Mritunjay, Deore Kalyani, Sonje Pranjal, Patil Kiran, Patil Rutuja

“…The system improves SBSP reliability, minimizes power loss, and forms a foundation for the development of autonomous SBSP infrastructure, which can be utilized to respond to different environmental challenges while providing energy transmission efficiency optimization.…”
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A lightweight and optimized deep learning model for detecting banana bunches and stalks in autonomous harvesting vehicles by Duc Tai Nguyen, Phuoc Bao Long Do, Doan Dang Khoa Nguyen, Wei-Chih Lin

“…Notably, the proposed model outperforms the previous detection models, offering high accuracy while optimizing computational efficiency. These advancements make the proposed model highly suitable for deployment on embedded systems in agricultural robots.…”
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Optimizing cervical cancer classification using transfer learning with deep gaussian processes and support vector machines by Emmanuel Ahishakiye, Fredrick Kanobe

“…These algorithms are (1) an optimized support vector machine (SVM), and (2) a deep Gaussian Process (DGP) model. …”
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Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification by Santhakumar D, Gnanajeyaraman Rajaram, Elankavi R, Viswanath J, Govindharaj I, Raja J

“…This work demonstrates the potential of hybrid optimization techniques in bioinformatics for better gene selection and cancer diagnosis. • Hybrid ACO-ALO approach combines strengths of both algorithms for better feature selection. • Enhances classifier performance while reducing computational complexity. • Outperforms traditional methods on leukemia prediction datasets.…”
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Optimization of Adaptive Observation Strategies for Multi-AUVs in Complex Marine Environments Using Deep Reinforcement Learning by Jingjing Zhang, Weidong Zhou, Xiong Deng, Shuo Yang, Chunwang Yang, Hongliang Yin

“…Traditional algorithms struggle with the strong coupling between environmental information and observation modeling, making it challenging to derive optimal strategies. …”
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Short-term scheduling optimization of battery electric buses in the context of sustainable energy resources under uncertainty by Muhammad Ahmad Iqbal, Ismail I. Almaraj

“…Consequently, the proposed framework effectively balances operational efficiency with resilience against price volatility, supporting reliable scheduling operations while optimizing renewable energy integration and enhancing grid flexibility.…”
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Utility-based optimization of Fujikawa's basket trial design - Pre-specified protocol of a comparison study. by Lukas D Sauer, Alexander Ritz, Meinhard Kieser

“…In a comparison study using simulations and numerical calculations, we are planning to investigate the use of utility functions for quantifying the compromise between power and type-I error inflation and the use of numerical optimization algorithms for optimizing these functions. …”
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Optimizing Economy with Comfort in Climate Control System Scheduling for Indoor Ice Sports Venues’ Spectator Zones Considering Demand Response by Zhuoqun Du, Yisheng Liu, Yuyan Xue, Boyang Liu

“…In terms of algorithm comparison, the performance of three typical multi-objective optimization algorithms—NSGA-II, standard MOEA/D, and Multi-Objective Brown Bear Optimization (MOBBO)—is systematically evaluated. …”
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Optimizing radiomics for prostate cancer diagnosis: feature selection strategies, machine learning classifiers, and MRI sequences by Eugenia Mylona, Dimitrios I. Zaridis, Charalampos Ν. Kalantzopoulos, Nikolaos S. Tachos, Daniele Regge, Nikolaos Papanikolaou, Manolis Tsiknakis, Kostas Marias, ProCAncer-I Consortium, Dimitrios I. Fotiadis

“…Key Points Radiomics is a growing field that can still be optimized. Feature selection method impacts radiomics models’ performance more than ML algorithms. …”
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Modeling of Global and Individual Kinetic Parameters in Wheat Straw Torrefaction: Particle Swarm Optimization and Its Impact on Elemental Composition Prediction by Ismael Urbina-Salas, David Granados-Lieberman, Martín Valtierra-Rodríguez, Claudia Adriana Ramírez-Valdespino, David Aarón Rodríguez-Alejandro

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Integrating Digital Twin and BIM for Special-Length-Based Rebar Layout Optimization in Reinforced Concrete Construction by Daniel Darma Widjaja, Jeeyoung Lim, Sunkuk Kim

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6G virtualized beamforming: a novel framework for optimizing massive MIMO in 6G networks by Ahmed M. Alwakeel

“…Our framework employs a combination of advanced machine learning algorithms and software-defined networking to dynamically allocate beamforming resources, improving adaptability in high-density environments and optimizing signal-to-noise ratios. …”
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Queen honey bee migration (QHBM) optimization for droop control on DC microgrid under load variation by Aripriharta Aripriharta, Mochammad Syarifudin Al Rasyid, Muhammad Cahyo Bagaskoro, Irham Fadlika, Sujito Sujito, Arif Nur Afandi, Saodah Omar, Norzanah Rosmin

“…Simulation results show that QHBM reaches an error of 0.8737 at the fourth iteration. The QHBM and PSO algorithms successfully optimized the performance of the DC microgrid under diverse loads, with QHBM converging in 5 iterations with an error of about 0.8737, and PSO in 40 iterations drawn error is 0.9 while keeping the current deviation less than 1.5 A and voltage error less than 0.5 V. …”
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From Fourier topology representation to optimal robot: evolution of an ultrahigh performance XYθ z nanopositioner by Zheng Lyu, Zilin Yang, Aiwu Zhou, Kang Tai, Guo Zhan Lum

“…Here we use a unique combination of kinematic analyses and evolutionary algorithms to determine our robot’s optimal geometry in which its structural topology is represented by Fourier basis functions. …”
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