Optimizing UAV Location for Deployment in Cell-Free Massive MIMO Networks Using a Soft Actor-Critic Reinforcement Learning by Okello Kenneth, Elijah Mwangi, Dominic Bernard Onyango Konditi

“…The uncrewed aerial vehicles (UAVs) communication network has recently garnered significant attention and motivation in academic and industrial research due to its flexible mobility concept in providing dynamic coverage in hotspot or congested areas with frequent user demand. While UAVs offer reliable connectivity in such challenging scenarios, integrating them with Cell-Free Massive MIMO (CF-mMIMO) networks presents severe issues in optimal deployment and coverage efficiency. …”
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Optimizing the train timetable in a high-speed rail corridor: The implications on departure time, fare cost and seat preference of passengers. by Zhipeng Huang, Limin Yang, Jinlian Li, Tao Zhang, Zixian Qu, Yusen Miao

“…A bi-level programming model is formulated: the upper level optimizes train operations and fare structures, while the lower level employs user equilibrium (UE) theory to distribute OD passenger demands across trains. …”
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Post-extrasystolic variation of ST segment and T wave as a mortality risk predictor after myocardial infarction by Ralf J. Dirschinger, Ralf J. Dirschinger, Alexander Müller, Petra Barthel, Alexander Steger, Michael Dommasch, Axel Bauer, Karl-Ludwig Laugwitz, Georg Schmidt, Daniel Sinnecker, Daniel Sinnecker

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Optimizing space heating efficiency in sustainable building design a multi criteria decision making approach with model predictive control by Zheng Qi, Nan Zhou, Xianwei Feng, Sama Abdolhosseinzadeh

“…Abstract Efficient space heating is vital for sustainable building design, offering opportunities to reduce energy consumption and costs while maintaining thermal comfort. This study examines the optimization of space heating in a nearly-zero energy building (nZEB) located in Oslo, Norway, under cold climatic conditions. …”
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Performance evaluation and multi-objective optimization of EDM parameters for Ti6Al4V using different tool electrodes by Manoj Jagdale, Masuk Abdullah, Nitin Ambhore, Atul Kulkarni, Rakesh Chaudhari, Jay Vora, József Menyhárt

“…Output responses—material removal rate (MRR), tool wear rate (TWR), surface roughness (SR), and dimensional deviation (DD)—were measured and optimized using the Teaching–Learning-Based Optimization (TLBO) algorithm. …”
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Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage by Yiwen Geng, Qi Liu, Hao Zheng, Shitong Yan

“…To address this, this paper proposes a two-stage power optimization method integrating rule-based allocation with algorithmic optimization for wind–solar hydrogen production systems, considering reserved energy storage. …”
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Carbon Policies and Liner Speed Optimization: Comparisons of Carbon Trading and Carbon Tax Combined with the European Union Emissions Trading Scheme by Ming Sun, Midakpe P. Vortia, Guangnian Xiao, Jing Yang

“…With the use of advanced optimization methods, such as the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and the Technique for Order of Preference by Similarity to an Ideal Solution (TOPSIS), this research explores the balance between adjusting vessel speeds and minimizing emissions. …”
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Reduced-Complexity and Robust Surface Water Path Delineation for Large Real-World Terrain Using Boundary Element Method by Ajalawit Chantaveerod, Kampol Woradit, Andrew Seagar, Thunyawat Limpiti

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A secure and energy-efficient routing using coupled ensemble selection approach and optimal type-2 fuzzy logic in WSN by S. Ambareesh, Pundalik Chavan, S. Supreeth, Rajesh Nandalike, P. Dayananda, S. Rohith

“…To deal with those challenges, we advocate a novel routing framework that is both steady and power-efficient, leveraging an Improved Type-2 Fuzzy Logic System (IT2FLS) optimized by means of the Reptile Search Algorithm (RSA). …”
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Intelligent Network-Level Energy Saving Strategy With STGNN-Driven Traffic Prediction and Path Optimization in Transport Networks and Field Trial by Xinyu Chen, Liuyan Han, Minxue Wang, Jiang Sun, Yong Gao, Xuegang Ou, Dechao Zhang, Han Li

“…Combined with K-shortest-path optimization algorithm, the system dynamically reallocates traffic to minimize active switch fabrics while maintaining strict service quality guarantees. …”
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Optimizing Geospatial Data for ML/CV Applications: A Python-Based Approach to Streamlining Map Processing by Removing Irrelevant Areas by David Kasperek, Michal Podpora

“…The research results of the paper reveal substantial file size reduction, and improved processing efficiency, thus making the optimized geospatial graphical data more practical for ML/CV applications, while still maintaining the original data quality and relevance of the analyzed parcels or infrastructure.…”
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Two-Stage Optimization of Mobile Energy Storage Sizing, Pre-Positioning, and Re-Allocation for Resilient Networked Microgrids with Dynamic Boundaries by Hongtao Lei, Bo Jiang, Yajie Liu, Cheng Zhu, Tao Zhang

“…Networked microgrids (NMGs) enhance the resilience of power systems by enabling mutual support among microgrids via dynamic boundaries. While previous research has optimized the locations of mobile energy storage (MES) devices, the critical aspect of MES capacity sizing has been largely neglected, despite its direct impact on costs. …”
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Double layers optimal scheduling of distribution networks and photovoltaic charging and storage station cluster based on leader follower game theory by Zixuan Liu, Jun Wu, Ruijin Zhu, Dewen Kong, Hao Guo

“…The upper layer takes the high-penetration distribution network as the decision-making entity and aims to maximize its own revenue while considering the energy trading of PCSSIS. The lower layer takes PCSSIS as the decision-making entity, and PCSSIS adjusts energy flow and optimizes revenue based on the internal electricity price provided by the upper-layer distribution network. …”
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Seismic Optimization of Fluid Viscous Dampers in Cable-Stayed Bridges: A Case Study Using Surrogate Models and NSGA-II by Qunfeng Liu, Zhen Liu, Jun Zhao, Yuhang Lei, Shimin Zhu, Xing Wu

“…The second strategy employs a data-driven surrogate model, specifically an Artificial Neural Network (ANN), integrated with the NSGA-II optimization algorithm. This surrogate model significantly reduced computational demands during the optimization process, offering a more efficient and scalable solution for the optimization process. …”
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QoE-Energy Consumption Optimization for End-User Devices in Adaptive Bitrate Video Streaming Using the Lagrange Multiplier Method by Tien Vu Huu, Thao Nguyen Thi Huong

“…Based on this function, an adaptive bitrate algorithm is proposed to select optimal video segments for video players, ensuring maximum QoE while minimizing energy consumption. …”
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Finding a New Balance Point: Intelligent Optimization of Multi-Target Cognitive Electronic Reconnaissance Strategy for Unmanned Aerial Vehicles by Yun Zhang, Shixun You, Yunbin Yan, Qiaofeng Ou, Xiang Zhu

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Addressing power quality challenges in hybrid renewable energy systems through STATCOM devices and advanced gray wolf optimization technique by Muhammed F. Alwaeli, Sadjad Galvani, Vahid Talavat

“…This algorithm acts to improve control parameters, thus increasing the system's reliability. …”
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Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response by Zhichun Yang, Lin Cheng, Huaidong Min, Yang Lei, Yanfeng Yang

“…Furthermore, the DRO framework achieves a superior balance between conservativeness and robustness over conventional stochastic and robust optimization methods, highlighting its potential to advance cost-effective, low-carbon energy systems while ensuring grid stability under uncertainty.…”
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Recurrent Neural-Based Vehicle Demand Forecasting and Relocation Optimization for Car-Sharing System: A Real Use Case in Thailand by Peerapon Vateekul, Panyawut Sri-iesaranusorn, Pawit Aiemvaravutigul, Adsadawut Chanakitkarnchok, Kultida Rojviboonchai

“…Finally, the Minimum Cost Maximum Flow algorithm is deployed to maximize forecasted demands, while minimizing the amount of relocations. …”
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Optimization of Adaptive I²H ∞ Control Method Based on Multiple Input Sensors by Yu Gu, Hanyang Li, Zeting Mei, Hao Wen, Yuanxiong Jin, Wenxuan Dong

“…The core contributions of this study include: 1) Designing a multi-sensor current reference estimator to dynamically generate the optimal electromagnetic torque through state variables such as wheel speed, acceleration, slope, and human factor database (heart rate, subjective score, fatigue index) to achieve real-time prediction of rider demand; 2) Proposing an adaptive current reference value estimation algorithm that integrates feedforward compensation and error feedback to ensure smooth switching of assistance modes and suppress sensor noise; 3) Developing an intention-induced H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> robust current tracking controller that significantly enhances the system&#x2019;s robustness to parameter fluctuations and external disturbances by optimizing the H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> norm of the closed-loop transfer function, while supporting personalized riding assistance.…”
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