Optimal operation for hybrid AC and DC systems under typhoon disaster considering branch switching and frequency security by Changfeng Liao, Li He, Zhuangxi Tan, Bin Xie, Yong Li, Chaoyang Chen, Yijia Cao

“…To address this issue, this paper proposes an optimal operation method for hybrid AC/DC systems with voltage source converters (VSCs) during extreme events. …”
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Artificial neural network analysis of Jeffrey hybrid nanofluid with gyrotactic microorganisms for optimizing solar thermal collector efficiency by Anup Kumar, Bhupendra K. Sharma, Bandar Almohsen, Laura M. Pérez, Kamil Urbanowicz

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GLTDNet: Cross-Domain Road Extraction Through Collaborative Optimization of Global-Local Feature Enhancement and Topological Decoupling by Jie Chen, Changxian He, Hao Wu, Jun Zhang, Siqiang Rao, Songshan Zhou, Jingru Zhu

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Optimization of distribution networks using quantum annealing for loss reduction and voltage improvement in electrical vehicle parking management by Naser Rashnu, Babak Mozafari, Reza Sharifi

“…This paper explores the integration of Electric Vehicle (EV) parking lots into power distribution networks (DNs) and proposes a quantum-based optimization framework to enhance grid performance. As EV and renewable energy source (RES) penetration increases, coordinated EV charging and discharging becomes critical for reducing power losses, improving voltage profiles, and supporting energy storage management. …”
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Flow Modeling in Pelton Turbines by an Accurate Eulerian and a Fast Lagrangian Evaluation Method by A. Panagiotopoulos, A. Židonis, G. A. Aggidis, J. S. Anagnostopoulos, D. E. Papantonis

“…Some commercial and open-source CFD codes, which implement Eulerian methods, have been validated against experimental results showing satisfactory accuracy. …”
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Risk–Cost Equilibrium for Grid Reinforcement Under High Renewable Penetration: A Bi-Level Optimization Framework with GAN-Driven Scenario Learning by Feng Liang, Ying Mu, Dashun Guan, Dongliang Zhang, Wenliang Yin

“…Spatial congestion maps and scenario risk-density plots further illustrate the ability of adversarial learning to reveal latent structural bottlenecks not captured by conventional methods. This work offers a new methodological paradigm, in which optimization and generative AI co-evolve to produce robust, data-aware, and stress-responsive transmission infrastructure designs.…”
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Inversion Method for Permitting Loadings of Pollutant from Lateral Effluents Based on Adjoint Equations by SHI Xiaoyan, ZHANG Hong, TAO Chunhua, LU Lingjiang, WAN Xin, LIU Zhaowei

“…However, optimization objectives that rely on discrepancies between predicted and observed concentrations cannot be directly applied to determine the permissible loadings, limiting the application of the adjoint equation method to this issue. …”
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Inversion Method for Permitting Loadings of Pollutant from Lateral Effluents Based on Adjoint Equations by SHI Xiaoyan, ZHANG Hong, TAO Chunhua, LU Lingjiang, WAN Xin, LIU Zhaowei

“…However, optimization objectives based on the discrepancies between predicted and observed concentrations cannot be straightforwardly employed for determining the permissible loadings, thus restricting the application of the adjoint equation method to this issue. …”
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Measurement and optimization paths of the multidimensional development levels of counties in the Yellow River Basin: based on the sustainable livelihoods framework by Lisha Cheng, Lisha Cheng, Li Ma, Jiajun Qiao, Jiajun Qiao, Xiaoyue Li

“…This is achieved by comprehensively utilizing geospatial, socio-economic, and other multi-source data in combination with methods such as the entropy weight method, the Theil index, and spatial analysis. …”
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DynaFusion-SLAM: Multi-Sensor Fusion and Dynamic Optimization of Autonomous Navigation Algorithms for Pasture-Pushing Robot by Zhiwei Liu, Jiandong Fang, Yudong Zhao

“…In the navigation accuracy test experiments, our proposed method reduces the root mean square error (RMSE) coefficient by 1.7% and Std by 2.7% compared with that of RTAB-MAP. …”
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Green-chemistry of by-products from Sai-Nam-Phueng orange in Thailand (1): Recovering a valuable source of bioactive compounds using response surface methodology, antioxidant, and... by Kanchanok Kodchakorn, Prachya Kongtawelert

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Gaussian Process Regression Total Nitrogen Prediction Based on Data Decomposition Technology and Several Intelligent Algorithms by WANG Yongshun, CUI Dongwen

“…Total nitrogen (TN) is one of the important indicators to reflect the degree of water pollution and measure the eutrophication status of lakes and reservoirs.To improve the accuracy of TN prediction,based on the empirical wavelet transform (EWT) and wavelet packet transform (WPT) decomposition technology,this paper proposes a Gaussian process regression (GPR) prediction model optimized by osprey optimization algorithm (OOA),rime optimization algorithm (ROA),bald eagle search (BES) and black widow optimization algorithm (BWOA) respectively.Firstly,the TN time series is decomposed into several more regular subsequence components by EWT and WPT respectively.Then,the paper briefly introduces the principles of OOA,ROA,BES,and BWOA algorithms and applies OOA,ROA,BES,and BWOA to optimize GPR hyperparameters.Finally,EWT-OOA-GPR,EWT-ROA-GPR,EWT-BES-GPR,EWT-BWOA-GPR,WPT-OOA-GPR,WPT-ROA-GPR,WPT-BES-GPR,WPT-BWOA-GPR models (EWT-OOA-GPR and other eight models for short) are established to predict the components of TN by the optimized super-parameters.The final prediction results are obtained after reconstruction,and WT-OOA-GPR,WT-ROA-GPR,WT-BES-GPR and WT-BWOA-GPR models based on wavelet transform (WT) are built.Eight models,including EWT-OOA-SVM based on support vector machine (SVM),the paper compares the unoptimized EWT-GPR,WPT-GPR models,and the uncomposed OOA-GPR,ROA-GPR,BES-GPR,and BWOA-GPR models.The models were verified by the monitoring TN concentration time series data of Mudihe Reservoir,an important drinking water source in China,from 2008 to 2022.The results are as follows.① The average absolute percentage error of eight models such as EWT-OOA-GPR for TN prediction is between 0.161% and 0.219%,and the coefficient of determination is 0.999 9,which is superior to other comparison models,with higher prediction accuracy and better generalization ability.② EWT takes into account the advantages of WT and EMD.WPT can decompose low-frequency and high-frequency signals at the same time.Both of them can decompose TN time series data into more regular modal components,significantly improving the accuracy of model prediction,and the decomposition effect is better than that of the WT method.③ OOA,ROA,BES,and BWOA can effectively optimize GPR hyperparameters and improve GPR prediction performance.…”
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Joint Classification of Hyperspectral and LiDAR Data via Multiprobability Decision Fusion Method by Tao Chen, Sizuo Chen, Luying Chen, Huayue Chen, Bochuan Zheng, Wu Deng

“…Finally, the four CPMs are fused via a multiprobability decision fusion method to obtain the optimal classification results. …”
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High Current Accelerator-driven Neutron Sources - The HBS project for a next generation neutron facility [version 2; peer review: 3 approved, 1 approved with reservations] by Ralf Gebel, Olaf Felden, Romuald Hanslik, Andreas Lehrach, Oliver Meusel, Yannick Beßler, Holger Podlech, Thomas Gutberlet, Thomas Brückel, Johannes Baggemann, Klaus Lieutenant, Jingjing Li, Ulrich Rücker, Eric Mauerhofer, Paul Zakalek, Jörg Voigt

“…Methods A project was launched at the Jülich Centre for Neutron Science for the development, design and demonstration of such an innovative high-current accelerator driven neutron source termed “High-Brilliance neutron Source” (HBS). …”
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High Current Accelerator-driven Neutron Sources - The HBS project for a next generation neutron facility [version 3; peer review: 3 approved, 1 approved with reservations] by Ralf Gebel, Olaf Felden, Romuald Hanslik, Andreas Lehrach, Oliver Meusel, Yannick Beßler, Holger Podlech, Thomas Gutberlet, Thomas Brückel, Johannes Baggemann, Klaus Lieutenant, Jingjing Li, Ulrich Rücker, Eric Mauerhofer, Paul Zakalek, Jörg Voigt

“…Methods A project was launched at the Jülich Centre for Neutron Science for the development, design and demonstration of such an innovative high-current accelerator driven neutron source termed “High-Brilliance neutron Source” (HBS). …”
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Efficiency and Driving Factors of Agricultural Carbon Emissions: A Study in Chinese State Farms by Guanghe Han, Jiahui Xu, Xin Zhang, Xin Pan

“…This study calculates the carbon emissions of state farms across 29 Chinese provinces using the IPCC method from 2010 to 2022. It also evaluates emission efficiency with the Super-Slack-Based Measure (Super-SBM model) and analyzes influencing factors using the Logarithmic Mean Divisia Index (LMDI) method. …”
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Numerical Solutions of the Mean‐Value Theorem: New Methods for Downward Continuation of Potential Fields by Chong Zhang, Qingtian Lü, Jiayong Yan, Guang Qi

“…Abstract Downward continuation can enhance small‐scale sources and improve resolution. Nevertheless, the common methods have disadvantages in obtaining optimal results because of divergence and instability. …”
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An Intelligent Method for C++ Test Case Synthesis Based on a Q-Learning Agent by Serhii Semenov, Oleksii Kolomiitsev, Mykhailo Hulevych, Patryk Mazurek, Olena Chernyk

“…Most traditional test suite optimization methods treat test cases as atomic units, without analyzing the utility of individual instructions. …”
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Comparison of methods for the quantification of cell-free DNA isolated from cell culture supernatant by Abel Jacobus Bronkhorst, Vida Ungerer, Stefan Holdenrieder

“…Although these are interesting findings, it can also be a great source of experimental confusion and emphasizes the importance of method optimization and standardization. …”
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The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market by Tang Xinfa, Wang Jingjing, Wang Yonghua, Wan Youwei

“…The method takes into account the characteristics and uncertainties of renewable energy sources such as solar and wind energy, and incorporates advanced multi-objective optimization algorithms. …”
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