Learning Rate Tuner with Relative Adaptation (LRT-RA): Road to Sustainable Computing by Saptarshi Biswas, Sumagna Dey, Subhrapratim Nath

“…Optimizing learning rates (LRs) in deep learning (DL) has long been challenging. …”
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Estimation and Reduction of CO₂ Emissions From Fossil Fuel Power Plants in Bangladesh by Deepak Kumar Chowdhury, Nur Mohammad, Tanjim Mahmud, Md. Khaliluzzaman, Karl Andersson, Mohammad Shahadat Hossain

“…The paper presents Matpower Interior Point Solver (MIPS), and Dynamic Non-Linear Particle Swarm Optimization (DNPSO) algorithms to solve combined economic emission dispatch (CEED) to optimize generation dispatch and minimize emissions. …”
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Bond behavior of galvanized iron fiber reinforced concrete with recycled coarse aggregate and model prediction using machine learning by Md. Jahidul Islam, Ummul Wara Labiba, Tasfiah Faisal Chowdhury, Md. Shahjalal, Tanvir Mustafy, Tanvir Hassan Tusher

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Low Signal-to-Noise Ratio Optoelectronic Signal Reconstruction Based on Zero-Phase Multi-Stage Collaborative Filtering by Xuzhao Yang, Hui Tian, Fan Wang, Jinping Ni, Rui Chen

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Multi-Agent Mapping and Tracking-Based Electrical Vehicles with Unknown Environment Exploration by Chafaa Hamrouni, Aarif Alutaybi, Ghofrane Ouerfelli

“…When rapid deliveries are required, the algorithm prioritizes faster routes, whereas, for flexible schedules, it optimizes energy conservation. …”
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A Frequency Hybrid Multi-mode PWM Modulation Method for SiC Traction Inverter by HU Liang, FU Xiangyu, LYU Yongcan, FENG Ling, HU Dong

“…In order to improve the efficiency of the traction system, this paper researches the PWM control strategy of high-frequency SiC traction inverter system from multiple dimensions such as inverter switching frequency optimization, modulation strategy selection and motor control algorithm adaptation. …”
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A Metaheuristic Framework for Cost-Effective Renewable Energy Planning: Integrating Green Bonds and Fiscal Incentives by Juan D. Saldarriaga-Loaiza, Johnatan M. Rodríguez-Serna, Jesús M. López-Lezama, Nicolás Muñoz-Galeano, Sergio D. Saldarriaga-Zuluaga

“…To do this, we use three optimization techniques to identify solutions that lower electricity generation costs: Teaching Learning, Harmony Search, and the Shuffled Frog Leaping Algorithm. …”
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Overcoming Fairness and Latency Challenges in BBR With an Adaptive Delay Detection by Zewei Han, Go Hasegawa

“…In 2016, Google introduced a new congestion control algorithm called Bottleneck Bandwidth and Round-trip propagation time (BBR). …”
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Сontrol of Intelligent Transport System in Minsk by D. V. Kapskiy, D. V. Navoy, P. A. Pegin

“…The paper considers algorithms for searching a maximum traffic volume of road vehicles in a traffic light cycle with a distributed intensity pulse and optimization of shifts under coordinated traffic flow control. …”
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Bio-Inspired Compliant Joints and Economic MPC Co-Design for Energy-Efficient, High-Speed Locomotion in Snake-like Robots by Shuai Zhou, Gengbiao Chen, Mingyu Gong, Jing Liu, Peng Xu, Binshuo Liu, Nian Yin

“…This study introduces a bio-inspired compliant joint design integrated with a hierarchical neural oscillator network and an energy-optimized control framework. The joint mimics biological skeletal flexibility using specialized wheeled mechanisms and adaptive parallel linkages, while the control network enables adaptive gait generation and seamless transitions through a phase-smoothing algorithm. …”
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Development of Model for Traffic Flows on Urban Street and Road Network by D. V. Kapskiy, D. V. Navoy, P. A. Pegin

“…Innovation in the first-level model is an approach in determining conditions while detecting a fuzzy set without using a standard algorithm that is an algorithm of local flexible regulation. …”
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Research on path planning for coal mine rescue robots by ZHU Hongbo, YIN Hongliang

“…This paper proposes a path planning method for coal mine rescue robots based on a Hierarchical Smooth Optimization Bidirectional A* guided dynamic window approach (HSTA*-G-DWA) algorithm. …”
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A Dual-Variable Selection Framework for Enhancing Forest Aboveground Biomass Estimation via Multi-Source Remote Sensing by Dapeng Chen, Hongbin Luo, Zhi Liu, Jie Pan, Yong Wu, Er Wang, Chi Lu, Lei Wang, Weibin Wang, Guanglong Ou

“…<i>langbianensis</i> forests, while GA-optimized machine learning models demonstrate excellent performance, providing strong support for regional-scale forest resource monitoring and carbon stock assessment.…”
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A Proposed Vision for Using Artificial Intelligence in Enhancing Strategic Value of Human Resources by Nadera Hourani

“…These benefits include efficiency gains, increased employee satisfaction, and strategic workforce optimization. Yet, there are significant challenges in the form of algorithmic bias, data privacy concerns, and organizational readiness. …”
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Electric Vehicle Energy Management Under Unknown Disturbances from Undefined Power Demand: Online Co-State Estimation via Reinforcement Learning by C. Treesatayapun, A. J. Munoz-Vazquez, S. K. Korkua, B. Srikarun, C. Pochaiya

“…The desired state of charge is defined as a reference trajectory, and the control input is computed while ensuring compliance with all operational constraints. …”
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An improved neurogenetic model for recognition of 3D kinetic data of human extracted from the Vicon Robot system by Ivan V. Stepanyan, Safa A. Hameed

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An optimized approach for predicting water quality features and a performance evaluation for mapping surface water potential zones based on Discriminant Analysis (DA), Geographical... by Abhijeet Das

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SABO-ELM model for remaining life prediction of lithium-ion batteries under multiple health factors by Jiabo LI, Zhonglin SUN, Di TIAN, Zhixuan WANG

“…The SABO algorithm optimizes the weights and bias thresholds of the ELM model, which effectively reduces the risk of local optima and improves its predictive performance and stability. …”
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VMD‐FBCCA classification method for SSVEP brain–computer interfaces by Ping Tan, Fengsheng Wang, Kaijun Zhou, Yi Shen

“…Next, a particle swarm algorithm is employed to optimize the weights of the IMFs and reconstruct the EEG signals. …”
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Prescribing the Future: The Role of Artificial Intelligence in Pharmacy by Hesham Allam

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