Enhanced COVID-19 Optimization Algorithm for Solving Multi-Objective Optimal Power Flow Problems with Uncertain Renewable Energy Sources: A Case Study of the Iraqi High-Voltage Gri... by Basim ALBaaj, Orhan Kaplan

“…This paper introduces an enhanced version, the enhanced COVID-19 optimization algorithm (ENHCOVIDOA), designed to improve the performance of the original method. …”
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Research on the Modelling and Analysis of the Penetration of Renewable Sources and Storage into Electrical Networks by Eva Simonič, Sebastijan Seme, Klemen Sredenšek

“…To address the growing integration of renewable energy sources and storage systems into distribution networks, there is a need for effective tools that can assess the impact of these technologies on grid performance. …”
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Flexible scheduling strategy for power systems considering source-load uncertainty by Qunmin YAN, Xiaoyu REN, Xiao SONG, Mengjue ZHAO, Chen AN

“…According to the characteristics of source-load uncertainty，the K-means method and robust optimization theory are combined to quantify the flexibility demand of the power system at multiple time scales. …”
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Optimizing the thermal treatment procedure using electrochemical methods to improve the performance of vanadium redox flow batteries by Mohammad Rahimi, Filippo Fenini, Anders Bentien

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Air-side Thermal-hydraulic Analysis and Parametric Optimization for Vertical-fin Microchannel Heat Exchanger by Zhao Rijing, Wei Xinghua, Huang Dong, Li Feng, Zhao Yongfeng

“…Finally, parametric optimization was conducted using the Taguchi method. …”
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Distribution Generation Network Arrangement by Capacitor Placement and Sizing in Renewable Energy Sources with Uncertainties Based on Self-adaption Kho-Kho Optimizer by Lu Xingxing

“…The arrangement of distributed generation networks through optimal capacitor placement and sizing is critical for modern power systems, particularly in the context of renewable energy sources with inherent uncertainties. …”
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A Source-load Low Carbon Optimization Methodology Considering Carbon Responsibility for Direct Carbon Emissions from Cement Plants by Jiang LI, Yuanzheng FAN, Bo LIU

“…Therefore, this paper proposes a source-load low-carbon optimization operation method that takes into account the direct carbon emission carbon responsibility of the cement plant to further improve the carbon responsibility apportionment. …”
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Retracted: Rearrangement of Electrical Distribution Networks With Optimal Coordination of Grid-Connected Hybrid Electric Vehicles and Wind Power Generation Sources by Javad Tabatabaei, Mahmoud Samiei Moghaddam, Javad Mohammadi Baigi

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A comprehensive review of dwell time optimization methods in computer-controlled optical surfacing by Tianyi Wang, Xiaolong Ke, Lei Huang, Qingqing Cui, Zili Zhang, Chunjin Wang, Hyukmo Kang, Weslin Pullen, Heejoo Choi, Daewook Kim, Vipender Negi, Qian Kemao, Yi Zhu, Stefano Giorgio, Philip Boccabella, Nathalie Bouet, Corey Austin, Mourad Idir

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Optimizing Biochar Concentration for Mitigating Nutrient Losses in Runoff: An Investigation into Soil Quality Improvement and Non-Point Source Pollution Reduction by Liqi Xing, Xiaoyin Niu, Xianwei Yin, Zhenhao Duan, Aiju Liu, Yanfei Ma, Peiling Gao

“…The use of biochar is an effective method to solve this problem. The aim of this study was to determine the optimal concentration of added biochar to reduce the soil particle, NH₄⁺ -N (AN), NO₃⁻ -N (NN), and total phosphorus (TP) losses. …”
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Assessing the Impact of Nutritional Knowledge and Information Sources on the Sports Performance of Elite Ethiopian Track Athletes: Insights for Optimized Sports Nutrition by Abdi Gudeta Taye, Ajita D Singh

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Review of Thermal Calculation Methods for Boilers—Perspectives on Thermal Optimization for Improving Ecological Parameters by Bartosz Ciupek, Andrzej Frąckowiak

“…A reasonable energy transition should be based on the direction of the thermal optimization of already functioning structures and adaptation of their operating parameters to the planned new ecological fuels in the sense of the intensification of energy converted from primary form to thermal energy, and in the last step, it should reorganize the energy and industrial sectors, leaving only these groups of devices treated as a stable and necessary source of energy. …”
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Multi-Source Data-Driven Terrestrial Multi-Algorithm Fusion Path Planning Technology by Xiao Ji, Peng Liu, Meng Zhang, Chengchun Zhang, Shuang Yu, Bing Qi, Man Zhao

“…This paper presents a multi-source data-driven hybrid path planning framework that integrates global A* search with local Deep Q-Network (DQN) optimization to address complex terrestrial routing challenges. …”
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A tutorial review of policy iteration methods in reinforcement learning for nonlinear optimal control by Yujia Wang, Xinji Zhu, Zhe Wu

“…Reinforcement learning (RL) has been a powerful framework for designing optimal controllers for nonlinear systems. This tutorial review provides a comprehensive exploration of RL techniques, with a particular focus on policy iteration methods for the development of optimal controllers. …”
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Probabilistic Optimization Method for Pilot-Bus Selection and Network Partitioning of AC/DC System by Wei YAN, Biao YANG, Jingshan MO, Youbin ZHOU, Tao WANG, Fan XIAO

“…To ensure higher voltage control ability of regional power supply to the converter bus, a probabilistic optimization method for pilot-bus selection and network partitioning of AC/DC system is proposed in this paper. …”
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Structural and transport properties of newly synthesized ZSM-5 sourcing silica from coconut shell ash by Aparna Sarker, Abu Sufian Rabbi, Nasrin Akter Nadi, A. K. M. Lutfor Rahman, A.A. Momin, Khondoker Shahin Ahmed, Hasina Akhter Simol

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Deep learning vulnerability detection method based on optimized inter-procedural semantics of programs by Yan LI, Weizhong QIANG, Zhen LI, Deqing ZOU, Hai JIN

“…In recent years, software vulnerabilities have been causing a multitude of security incidents, and the early discovery and patching of vulnerabilities can effectively reduce losses.Traditional rule-based vulnerability detection methods, relying upon rules defined by experts, suffer from a high false negative rate.Deep learning-based methods have the capability to automatically learn potential features of vulnerable programs.However, as software complexity increases, the precision of these methods decreases.On one hand, current methods mostly operate at the function level, thus unable to handle inter-procedural vulnerability samples.On the other hand, models such as BGRU and BLSTM exhibit performance degradation when confronted with long input sequences, and are not adept at capturing long-term dependencies in program statements.To address the aforementioned issues, the existing program slicing method has been optimized, enabling a comprehensive contextual analysis of vulnerabilities triggered across functions through the combination of intra-procedural and inter-procedural slicing.This facilitated the capture of the complete causal relationship of vulnerability triggers.Furthermore, a vulnerability detection task was conducted using a Transformer neural network architecture equipped with a multi-head attention mechanism.This architecture collectively focused on information from different representation subspaces, allowing for the extraction of deep features from nodes.Unlike recurrent neural networks, this approach resolved the issue of information decay and effectively learned the syntax and semantic information of the source program.Experimental results demonstrate that this method achieves an F1 score of 73.4% on a real software dataset.Compared to the comparative methods, it shows an improvement of 13.6% to 40.8%.Furthermore, it successfully detects several vulnerabilities in open-source software, confirming its effectiveness and applicability.…”
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Enhancement method of series hybrid ship energy efficiency for speed and energy collaborative optimization by Yupeng Yuan, Xiaoyu Wang, Liang Tong, Chengqing Yuan, Boyang Shen, Teng Long

“…Our findings demonstrated that this optimization method can distribute the output of the power source in a better way, thereby optimising the speed of the vessel and maintaining stable sailing. …”
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A dual-layer planning method based on improved MOPSO for distribution networks considering source–load temporal uncertainty by Guilian Wu, Guilian Wu, Jia Lin, Jinlin Liao

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Multi-Timescale Battery-Charging Optimization for Electric Heavy-Duty Truck Battery-Swapping Stations, Considering Source–Load–Storage Uncertainty by Peijun Shi, Guojian Ni, Rifeng Jin, Haibo Wang, Jinsong Wang, Zhongwei Sun, Guizhi Qiu

“…With the widespread adoption of renewable energy sources like wind power and photovoltaic (PV) power, uncertainties in the renewable energy output and the battery-swapping demand for electric heavy-duty trucks make it challenging for battery-swapping stations to optimize battery-charging management centrally. …”
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