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Insulator defect detection under extreme weather based on synthetic weathera* algorithm and improved YOLOv7

High Voltage 2025年第1期10卷 69-77页

作者： Yong Yang Shuai Yang Chuan Li Yunxuan Wang Xiaoqian Pi Yuxin Lu Ruohan Wu State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical Engineering and ElectronicsHuazhong University of Science and TechnologyWuhanChina State Grid Hunan Electric Power Company ChangshaChina

Efficient and accurate insulator defect detection is essential for maintaining the safe and stable operation of transmission ***,the detection effectiveness is adversely impacted by complex and changeable environmental backgrounds,particularly under extreme weather that elevates accident ***,this research proposes a high-precision intelligent strategy based on the synthetic weathera* algorithm and improved YOLOv7 for detecting insulator defects under extreme *** proposed meth-odology involves augmenting the dataset with synthetic rain,snow,and foga* algorithm ***,the original dataset undergoes augmentation through affine and colour transformations to improve model's generalisation performance under complex power inspection *** achieve higher recognition accuracy in severe weather,an improved YOLOv7a* algorithm for insulator defect detection is proposed,integrating focal loss with SIoU loss function and incorporating an optimised decoupled head *** results indicate that the synthetic weathera* algorithm processing significantly improves the insulator defect detection accuracy under extreme weather,increasing the mean average precision by 2.4%.Furthermore,the authors’improved YOLOv7 model achieves 91.8%for the mean average precision,outperforming the benchmark model by 2.3%.With a detection speed of 46.5 frames per second,the model meets the requirement of real-time detection of insulators and their defects during power inspection.

关键词： weather extreme algorithm

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Wave effect of gravitational waves intersected with a microlens field II:An adaptive hierarchical treea* algorithm and population study

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Science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 237-250页

作者： Xikai Shan Guoliang Li Xuechun Chen Wen Zhao Bin Hu Shude Mao Purple Mountain Observatory Chinese Academy of SciencesNanjing 210023China Department of Astronomy Tsinghua UniversityBeijing 100084China Institute for Frontier in Astronomy and Astrophysics Beijing Normal UniversityBeijing 102206China School of Physics and Astronomy Beijing Normal UniversityBeijing 100875China School of Astronomy and Space Science University of Science and Technology of ChinaHefei 230026China CAS Key Laboratory for Researches in Galaxies and Cosmology Department of AstronomyUniversity of Science and Technology of ChinaChinese Academy of SciencesHefei 230026China

The gravitational lensing wave effect generated by a microlensing field embedded in a lens galaxy is an inevitable phenomenon in strong lensed gravitational waves(SLGWs).This effect presents both challenges and opportunities for the detection and appli-cation of ***,investigating this wave effect requires computing a complete diffraction integral over each microlens in the *** is extremely time-consuming due to the large number of microlenses(10^(3)-10^(6)).Therefore,simply adding all the microlenses is ***,the complexity of the time delay surface makes the lens plane resolution a crucial factor in controlling numerical *** this paper,we propose a trapezoid approximation-based adaptive hierarchical tree algo-rithm to meet the challenges of calculation speed and *** find that thisa* algorithm accelerates the calculation by four orders of magnitude compared to the simple adding method and is one order of magnitude faster than the fixed hierarchical treea* algorithm proposed for electromagnetic *** importantly,oura* algorithm ensures controllable numerical errors,increasing confidence in the *** with our previous work(***.66,239511,2023),this paper addresses all numerical issues,including integral convergence,precision,and computational time1).Finally,we conducted a population study on the microlensing wave effect of SLGWs using thisa* algorithm and found that the microlensing wave effect cannot be ignored,especially for Type II SLGWs(from saddle position of the time delay surface)due to their intrinsic geometric structures and their typical intersection with a denser microlensing ***,more than 33%(11%)of SLGWs have a mismatch larger than 1%(3%)compared to the unlensed ***,we found that the mismatch between signal pairs in a doubly imaged GW is generally larger than 10^(−3),and 61%(25%)of signal pairs have a mismatch larger than 1%(3%).Theref

关键词： gravitational lensing diffractional integral algorithm gravitational wave

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Optimal Routing in Urban Road Networks: A Graph-Based Approach Using Dijkstra'sa* algorithm

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APPLIED SCIENCES-BASEL 2025年第8期15卷 4162-4162页

作者： Grujic, Zarko Grujic, Bojana Univ Banja Luka Fac Architecture Civil Engn & Geodesy Dept Civil Engn Bulevar Petra Bojovica 1A Banja Luka 78000 Bosnia & Herceg

This paper presents a new approach to optimizing route selection in urban road networks with sparsely placed traffic counters. By leveraging graph theory and Dijkstra'sa* algorithm, we propose a new method to determine the shortest path between origins and destinations in city traffic networks with sparsely placed counters. The method is based on the similarities between traffic flows recorded at the counter and the streets that generate traffic for a given counter. The advantage of this method is the use of a secondary counter function to obtain data that are built into the shortest path determination model and the free choice of the time of day for which the path is searched. The proposed method is implemented using the programming language AutoLISP 2022 and program AutoCAD 2022, providing a valuable tool for transportation engineers and urban planners. This paper presents a model of the shortest path that integrates one-way streets, the average speed of the car, as well as the delay time at traffic-lighted and non-traffic intersections. The model was applied to the traffic network of the city of Sarajevo (Bosnia and Herzegovina), but there are no restrictions for application to any network equipped with traffic counters. The obtained results show a high agreement with the Google Maps service as a reference system.

关键词： transport network transportation planning route optimization graph theory algorithm shortest path in a graph traffic counters

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An improved meta-heuristica* algorithm for energy optimization in smart grids considering photovoltaic, storage battery, and demand response

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JOURNAL OF ENERGY STORAGE 2025年 119卷

作者： Hafeez, Ghulam Ullah, Safeer Islam, Mazhar Khan, Farrukh Aslam Alsafran, Ahmed S. Alghamdi, Baheej Kraiem, Habib Univ Engn & Technol Dept Elect Engn Mardan 23200 Pakistan Quaid E Azam Coll Engn & Technol Dept Elect Engn Sahiwal 57000 Pakistan Shenzhen Univ China Coll Elect & Informat Engn Shenzhen 518060 Guangdong Peoples R China King Saud Univ Ctr Excellence Informat Assurance Riyadh 11653 Saudi Arabia Univ Tenaga Nas Coll Comp & Informat Kajang 43000 Selangor Malaysia King Faisal Univ Coll Engn Dept Elect Engn Al Hasa Saudi Arabia King Abdulaziz Univ Ctr Res Excellence Renewable Energy & Power Syst Smart Grids Res Grp Jeddah 21589 Saudi Arabia King Abdulaziz Univ Fac Engn Dept Elect & Comp Engn Jeddah 21589 Saudi Arabia Northern Border Univ Ctr Sci Res & Entrepreneurship Ar Ar 73213 Saudi Arabia

Residential load scheduling in smart power grids (SPGs), especially those incorporating renewable energy sources (RESs), storage battery, and demand response (DR) faces significant challenges due to the limitations of traditional optimizationa* algorithms. These challenges include premature convergence, high computational costs, imbalanced exploration and exploitation, lack of adaptability, and sensitivity to parameters. Such issues make it difficult to effectively manage energy consumption, alleviate peak loads, and reduce energy costs while maintaining user comfort. To address these challenges, we propose an improved particle swarm optimization (IPSO)a* algorithm that enhances exploration and exploitation balance through inertia weight adjustment, velocity damping, and the inclusion of crossover and mutation strategies. These enhancements prevent premature convergence and allow for faster, more accurate convergence to optimal solutions. The proposed IPSO is integrated into a power usage scheduler (PUS) for optimal residential load scheduling under an adaptive pricing scheme considering photovoltaic (PV) and storage battery, focusing on reducing peak energy usage, rebound peaks, energy costs, and user discomfort. The effectiveness of the IPSO-based PUS is demonstrated through a comparison with other optimizationa* algorithms such as genetic optimizationa* algorithm (GOA), particle swarm optimization (PSO), and wind-driven optimization (WDO). Results show that the IPSOa* algorithm consistently outperforms these alternatives in terms of energy consumption, peak energy alleviation, cost reduction, and grid stability, while also achieving faster execution times and superior convergence rates. This work provides a robust solution for residential load scheduling, offering significant insights and practical benefits for energy optimization in SPGs.

关键词： Demand response Distributed generation Energy storage Power usage scheduling Improved particle swarm optimization algorithm Storage battery Smart power grid

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A discrete water source cyclea* algorithm design for solving production scheduling problem in flexible manufacturing systems

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SWARM AND EVOLUTIONARY COMPUTATION 2025年 94卷

作者： Xu, Wenxiang Xu, Shimin Liang, Junyong Qin, Tao Liu, Dezheng Wang, Lei Hubei Univ Arts & Sci Hubei Longzhong Lab Xiangyang 441000 Peoples R China Sichuan Univ Sci & Engn Sch Civil Engn Zigong 643000 Peoples R China Wuhan Univ Technol Sch Mech & Elect Engn Wuhan 430070 Peoples R China

Aiming at solving the production scheduling problems in flexible manufacturing systems including the flexible job shop scheduling (FJSP) and distributed flexible job shop scheduling (DFJSP) with operation outsourcing, which are two kinds of typical NP-hard problems, the general mathematical model with two optimization objectives including minimizing the total costs as well as makespan are developed. Then, an innovative discrete water source cyclea* algorithm (IDWCA) inspired by the water cycle process is proposed to address the model. In the IDWCA, the operators including evaporation mixing, precipitation, local mixing, modification of water source composition and water source loss are designed to search for optimization solutions. Finally, 15 FJSP comparison experiments and 45 DFJSP comparison experiments with different scales are provided to verify the comprehensive performance of the IDWCA, in which the IDWCA, the original water cyclea* algorithm (OWCA), and the two general meta-heuristica* algorithms genetica* algorithm (GA) and particle swarm optimization (PSO) are involved. Compared with OWCA, GA and PSO, IDWCA performs significantly better in all FJSP experiments, while it performs better in 43 out of 45 DFJSP experiments, and its advantages are more significant in solving the medium-scale and large-scale problems. In addition, the evolutionary curves of the abovea* algorithms indicate that the IDWCA has the better convergence speed and results than that of OWCA, GA and PSO. Therefore, the developed mathematical model and IDWCA are effective in solving the studied FJSP and DFJSP, the proposeda* algorithm enriches the theoretical researches on meta-heuristica* algorithms and production scheduling.

关键词： Flexible job shop scheduling Distributed flexible job shop scheduling Operation outsourcing Innovative discrete water source cycle algorithm Multi-objective optimization

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A new intelligent prediction model using machine learning linked to grey wolf optimizera* algorithm for O2/N2 adsorption

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CANADIAN JOURNAL OF CHEMICAL ENGINEERING 2025年第3期103卷 1229-1245页

作者： Mashhadimoslem, Hossein Kermani, Vahid Zanganeh, Kourosh Shafeen, Ahmed Elkamel, Ali Univ Waterloo Chem Engn Dept Waterloo ON N2L 3G1 Canada Nat Resources Canada NRCan CanmetENERGY Ottawa CE O Ottawa ON Canada Khalifa Univ Dept Chem Engn Abu Dhabi U Arab Emirates

To address the deficiency and predict the adsorption performance in different adsorbents, this study proposes a new optimizer linked to the machine learning (ML) model considering the performance of the adsorption process. The main goal is to predict adsorption under different process conditions with different adsorbents and provide a unified framework, leading to the prediction of adsorption phenomena instead of traditional isotherm models. This research focuses on predicting the adsorbed amount of O2 and N2 on several carbon-based adsorbents using the ML approach linked to the grey wolf optimizera* algorithm (GWO). Experimental isotherm data (dataset 1344) on adsorbent type, temperature, pressure, gas type, and adsorption capacity of the process adsorption were used as input and output datasets. The besta* algorithm was Broyden-Fletcher-Goldfarb-Shanno (BFGS), a two-layer network from a multi-layer perceptron (MLP) method applying 28 neurons. The new MLP-GWO network would have the best mean square error (MSE) efficiencies of 0.00037, while the R2 (r-squared) was 0.9934. The new ML-generated model can accurately predict the adsorption process behaviour of different carbon-based adsorbents under various process conditions. The results of this research have the potential to assist a wide range of gas separation industries.

关键词： adsorption algorithm gas separation grey wolf optimizer MLP

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Emergency evacuation risk assessment for toxic gas attacks in airport terminals: Model,a* algorithm, and application

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2025年 253卷

作者： Luan, Tianyi Gai, Wenmei Sun, Diange Dong, Hao China Univ Geosci Beijing Sch Engn & Technol Beijing 100083 Peoples R China China Univ Ind Relat Inst Safety Engn Beijing 100048 Peoples R China

Transportation infrastructure has often been the target of terrorist attacks, and mitigation of the risk of toxic gas attacks is a challenging task in the design of indoor emergency evacuation systems. Considering multiple emergency response modes, we propose an agent-based risk assessment model and itsa* algorithm to integrate gas diffusion and pedestrian movement data for emergency response, quickly assessing average individual exposure risk. We assessed the exposure status of individuals with respect to their emergency response actions following a toxic gas attack in an airport terminal. The results indicate that in the event of a general gas attack on an airport terminal, ventilation must be immediately ceased along with early evacuation. In areas with a shelter-in-place environment, the ventilation mode and shelter-in-place time should be determined based on the concentration of indoor and outdoor gases. In areas with nerve gas exposure and high population density, a new exit must be established at evacuation bottlenecks, and pedestrians must be guided to evacuate while promptly closing ventilation. These results offer suggestions and strategies for emergency response and decision-making in airport terminals during such incidents.

关键词： Emergency management Individual response Airport terminal Toxic gas attack Risk assessment algorithm

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Joint inverse analysis for instantaneous and creep deformation parameters of high rockfill dams based on surrogate models and improved multi-objective intelligenta* algorithm

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 277卷

作者： Yu, Jia ao Sun, Yiqing Shen, Zhenzhong Gan, Lei Hohai Univ Coll Water Conservancy & Hydropower Engn Nanjing 210024 Peoples R China Minist Transport Key Lab Transport Ind Comprehens Transportat Theor Nanjing Modern Multimodal Transportat Lab Nanjing 211100 Peoples R China Hohai Univ State Key Lab Hydrol Water Resources & Hydraul Eng Nanjing 210024 Peoples R China Southeast Univ Sch Transportat Nanjing 211189 Peoples R China

The monitoring data analysis and numerical calculation for the deformation of earth rock dams are essential basis for structural state assessment. However, due to the complexity of high rockfill dam, conventional finite element (FE) calculation and inverse analysis methods are often difficult to accurately reconstruct the deformation field of the dam body. In this paper, the improved multi-objective cuckoo search (IMOCS)a* algorithm was combined with the response surface model (RSM) to perform multi-objective joint inverse analysis for instantaneous and creep deformation parameters of a high rockfill dam, which is verified to have superiorities in aspects of iteration efficiency, coverage and uniformity of solution sets. Eventually, the reasonable mechanical parameters of rockfill material were obtained, and the settlement process of dam monitoring points was simulated. Unlike the conventional single objective method, the proposed novel method can avoid three issues including the difficulty of separating instantaneous deformation and creep, the inconsistency of buried and start measuring time for deformation monitors, and the neglection for the effect of water level changes during operation. In conclusion, the proposed approach possesses the potential of precise identification for mechanical parameter and the advantage in facilitating the assessment of structural safety for earth rock dams.

关键词： High core rockfill dam Joint inverse analysis Settlement monitoring Surrogate model Improved multi-objective cuckoo search algorithm

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The Application of the Convective-Stratiform Classificationa* algorithm for Feature Detection in Polarimetric Radar Variables and QPE Retrieval During Warm-Season Convection

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REMOTE SENSING 2025年第7期17卷 1176-1176页

作者： Mikidadi, Ndabagenga Daudi Huang, Xingyou Bu, Lingbing Nanjing Univ Informat Sci & Technol Sch Atmospher Phys Nanjing 210044 Peoples R China Tanzania Meteorol Author Forecasting Off Kilimanjaro Int Airport Hai POB 03 Kilimanjaro Tanzania

Feature detection is one of the hot topics in the weather radar research community. This study employed a convective-stratiform classificationa* algorithm to detect features in polarimetric radar variables and Quantitative Precipitation Estimation (QPE) retrieval during a heavy precipitation event in Crossville, Tennessee, during warm-season convection. Analysis of polarimetric radar variables revealed that strong updrafts, mixed-phase precipitation, and large hailstones in the radar resolution volume during the event were driven by the existence of supercell thunderstorms. The results of feature detection highlight that the regions with convective-stratiform cores and strong-faint features in the reflectivity field are similar to those in the rainfall field, demonstrating how thea* algorithm more effectively detects features in both fields. The results of the estimates, accounting for uncertainty during feature detection, indicate that an offset of +2 dB overestimated convective features in the northeast in both the reflectivity and rainfall fields, while an offset of -2 dB underestimated convective features in the northwest part of both fields. The results highlight that convective cores cover a small area with high rainfall exceeding 50 mmh-1, while stratiform cores cover a larger area with greater horizontal homogeneity and lower rainfall intensity. These findings are significant for nowcasting weather, numerical models, hydrological applications, and enhancing climatological computations.

关键词： weather radar feature detection polarimetric variables QPE algorithm

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Efficient Contacta* algorithm for 3D Finite Element Modeling of Bottomhole Assemblies: Validation and Application

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SPE JOURNAL 2025年第3期30卷 1237-1255页

作者： Zhang, He Tian, Kaixiao Bhaidasna, Ketan Halliburton Houston TX 77032 USA

Static analysis of the lateral deformation of a bottomhole assembly (BHA) is essential for controlling borehole trajectories in directional drilling. A major technical challenge in static BHA modeling is efficiently determining the contact configuration between the BHA and the borehole wall. This configuration, including contact locations and orientations, is not known a priori and introduces nonlinearities into the analysis. Mosta* algorithms addressing the contact problem in BHA modeling are proprietary and lack detailed descriptions. Explicita* algorithms based on the Newton-Raphson iteration method and linear/nonlinear complementarity problem formulations have limitations, such as computational inefficiency and the need for predefined contact locations. In this paper, we derive governing differential equations for 3D BHA static deformation, incorporating nonlinear effects from borehole curvature, axial forces, and both discrete and continuous contacts. The finite element method (FEM) is used to solve these equations under appropriate boundary conditions. Within the finite element framework, the Lagrange multiplier method (LMM) is used to impose displacement constraints at contact points, while an innovative iterative process ensures the unilateral nature of the contacts. Thea* algorithm typically converges in O (10) each iteration involving the solution of approximately O (10(2)) iterations, with finite element equations, ensuring high computational efficiency. Thea* algorithm, grounded in principles of structural mechanics, is robust across a wide range of conditions, and its accuracy is validated against a publisheda* algorithm. The proposed BHA model is further validated using downhole measurements. In one scenario, bending moment on bit (BOB) measurements from a BHA equipped with a rotary steerable system (RSS) shows strong agreement with the model results, both in magnitude and variation pattern, when a fixed displacement boundary condition is applied at the bit. In

关键词： geology contact point drilling operation trajectory design geologist directional drilling drillstring design deformation algorithm bit side force

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