Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment by Jing Zhang, Jingjing Liu, Zhong Wan

“…For this complicated polymorphic uncertain optimization model, a unified compromising approach is proposed to hedge the uncertainty of this model such that some powerful optimization algorithms can be applied to make an optimal recycling plan. …”
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Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management by William Alberto Cruz Castañeda, Pedro Bertemes Filho

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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…This paper presents an enhanced hybrid particle swarm optimization (EHPSO) algorithm that incorporates a spatial position encoding (SPE) strategy to optimize coverage while dynamically adjusting the number of sensors deployed in WSNs. …”
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UV-Vis spectroscopy coupled with firefly algorithm-enhanced artificial neural networks for the determination of propranolol, rosuvastatin, and valsartan in ternary mixtures by Ahmed Serag, Maram H. Abduljabbar, Yusuf S. Althobaiti, Farooq M. Almutairi, Shaker T. Alsharif, Rami M. Alzhrani, Marwa F. Ahmed, Atiah H. Almalki

“…An experimental design of 25 samples was employed as a calibration set, and a central composite design of 20 samples was used as a validation set. The firefly algorithm (FA) was evaluated as a variable selection procedure to optimize the developed ANN models resulting in simpler models with improved predictive performance as evident by lower relative root mean square error of prediction (RRMSEP) values compared to the full spectrum ANN models. …”
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Optimized Software Implementation of Keccak, Kyber, and Dilithium on RV{32,64}IM{B}{V} by Jipeng Zhang, Yuxing Yan, Junhao Huang, Çetin Kaya Koç

“… With the standardization of NIST post-quantum cryptographic (PQC) schemes, optimizing these PQC schemes across various platforms presents significant research value. …”
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Enhancing Supply Chain Agility and Sustainability through Machine Learning: Optimization Techniques for Logistics and Inventory Management by Vikram Pasupuleti, Bharadwaj Thuraka, Chandra Shikhi Kodete, Saiteja Malisetty

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Flexibility Resource Planning and Stability Optimization Methods for Power Systems with High Penetration of Renewable Energy by Haiteng Han, Xiangchen Jiang, Yang Cao, Xuanyao Luo, Sheng Liu, Bei Yang

“…Furthermore, to mitigate the uncertainty and fault risks associated with extreme weather events, a CVaR-based risk quantification framework is incorporated into a bi-level optimization model, effectively balancing investment costs and operational risks under uncertainty. …”
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An adaptive differential evolution algorithm to solve the multi-compartment vehicle routing problem: A case of cold chain transportation problem by Supaporn Sankul, Naratip Supattananon, Raknoi Akararungruangkul, Narong Wichapa

“…The ADE algorithm aims to minimize the total cost, which includes both the expenses for traveling and using the vehicles. …”
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Multi-Objective Optimization of Offshore Wind Farm Configuration for Energy Storage Based on NSGA-II by Xin Lin, Wenchuan Meng, Ming Yu, Zaimin Yang, Qideng Luo, Zhi Rao, Jingkang Peng, Yingquan Chen

“…How to achieve effective wind power stabilization at the lowest cost has become a key issue. This paper proposes three different energy storage configuration strategies and adopts the non-dominated sorting genetic algorithm (NSGA-II) to conduct multi-objective optimization of the system. …”
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Optimization of Urban Rail Transit Train Stock Utilization under Re-coupling Operation Mode by DENG Chengyuan, LU Jinsheng, ZHU Changfeng, SUN Yuanguang, MA Bin

“…In the case study of a certain urban rail transit line with significant imbalance of passenger flow in different periods, the feasibility and rationality of the above optimized model are verified. ［Result & Conclusion］ The optimized train stock utilization scheme of urban rail transit under the re-coupling operation mode can reasonably optimize the connection between different marshalling train trips and reduce the operation costs for enterprises.…”
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Multi-Agent Deep Reinforcement Learning for Scheduling of Energy Storage System in Microgrids by Sang-Woo Jung, Yoon-Young An, BeomKyu Suh, YongBeom Park, Jian Kim, Ki-Il Kim

“…To defeat the above issues, in this paper, we propose a new DRL-based scheduling algorithm using a multi-agent proximal policy optimization (MAPPO) framework that is combined with Pareto optimization. …”
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Application of High Efficiency and High Precision Network Algorithm in Thermal Capacity Design of Modular Permanent Magnet Fault-Tolerant Motor by Yunlong Yi, Sheng Ma, Bo Zhang, Wei Feng

“…Aiming at the problems of low thermal analysis efficiency and high computational cost of traditional computational fluid dynamics (CFD) methods for modular fault-tolerant permanent magnet synchronous motors (MFT-PMSMs) under complex working conditions, this paper proposes a fast modeling and calculation method of motor temperature field based on a high-efficiency and high-precision network algorithm. …”
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Methods for Improving Point Cloud Authenticity in LiDAR Simulation for Autonomous Driving: A Review by Yanzhao Yang, Jian Wang, Xinyu Guo, Xinyu Yang, Wei Qin

“…It also proposes future directions to bridge the gap between simulated and real-world data, aiming to optimize hybrid training models for improved autonomous driving applications.…”
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Human-Centric IoT-Driven Digital Twins in Predictive Maintenance for Optimizing Industry 5.0 by Özlem Sabuncu, Bülent Bilgehan

“…The framework uses an enhanced particle swarm optimization (PSO) algorithm to reconcile competing goals, including maintaining operator safety, optimizing asset reliability, and minimizing maintenance costs. …”
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Optimizing multimodal timetable synchronization of intercity railway and metro for the first service period during holidays by Yan Liu, Quan Zhang, Xuan Li, Yang Shi

“…To solve the model, an improved artificial bee colony algorithm (ABC) is designed, incorporating adaptive neighbour search and simulated annealing techniques. …”
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Forecasting the vapor pressure deficit in vertical farming facilities aiming to provide optimal indoor conditions by Carlos Alejandro Perez Garcia, Dafni Despoina Avgoustaki, Enrica Santolini, Daniele Torreggiani, Thomas Bartzanas, Patrizia Tassinari, Marco Bovo

“…The model, demonstrating satisfactory performance in predicting VPD, enables optimization of indoor growth conditions, thereby improving resources use efficiency and minimizing operational costs. …”
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Deep reinforcement learning-based resource joint optimization for millimeter-wave massive MIMO systems by LIU Qingli, LI Xiaoyu, LI Rui

“…Experimental results show that the proposed joint optimization method significantly improves the throughput and energy efficiency of the system compared with the single-stage all-digital precoding and hybrid precoding equal resource allocation methods and the particle swarm optimization-based resource allocation algorithm.…”
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Vibration Analysis and Optimization of Iron-Core Reactors Based on Fe-Based Soft Magnetic Composite Materials by Yangyang Ma, Wenle Song, Jie Gao, Yang Liu, Yilei Shang, Weimei Zhao, Fuyao Yang

“…The characteristic parameters of the improved model are identified using the particle swarm optimization–simulated annealing (PSO-SA) algorithm, with the identified root mean square error not exceeding 3.5, verifying the model’s accuracy. …”
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Optimization Configuration Method of Energy Storage Considering Photovoltaic Power Consumption and Source-Load Uncertainty by Junjie Qiao, Xiaofang Meng, Weigang Zheng, Pengxue Huang, Tiefeng Xu, Yupeng Xu

“…The constraints, including node voltage and energy storage device, are considered, and the model is solved using the improved grey wolf optimization algorithm. Finally, a distribution network station system is employed to compare and analyze the capacity allocation results of poor operation scenarios under different schemes, the results showed that after energy storage optimization, the voltage of each scheme decreased from 0.4869kV to 0.42kV, and the curtailment rate decreased by 13.09%, 21.33%, and 23.69% respectively compared to before optimization,which verifies the effectiveness of the models and methods proposed in this paper.…”
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A Hybrid Model Integrating Variational Mode Decomposition and Intelligent Optimization for Vegetable Price Prediction by Gao Wang, Shuang Xu, Zixu Chen, Youzhu Li

“…This study proposes a hybrid forecasting model integrating variational mode decomposition (VMD), the Fruit Fly Optimization Algorithm (FOA), and a gated recurrent unit (GRU). …”
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