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Short-TermWind Power Forecast Based on STL-IAOA-iTransformer Algorithm:A Case Study in Northwest China

Energy engineering 2025年第2期122卷 405-430页

作者： Zhaowei Yang Bo Yang Wenqi Liu Miwei Li Jiarong Wang Lin Jiang Yiyan Sang Zhenning Pan Faculty of Science Kunming University of Science and TechnologyKunming650500China Faculty of Electric Power engineering Kunming University of Science and TechnologyKunming650500China department of electrical engineering and Electronics University of LiverpoolLiverpoolL693GJUK College of electrical engineering Shanghai University of Electric PowerShanghai200090China School of Electric Power engineering South China University of TechnologyGuangzhou510640China

Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart *** numerous studies have employed various methods to forecast wind power,there remains a research gap in leveraging swarm intelligence algorithms to optimize the hyperparameters of the Transformer model for wind power *** improve the accuracy of short-term wind power forecast,this paper proposes a hybrid short-term wind power forecast approach named STL-IAOA-iTransformer,which is based on seasonal and trend decomposition using LOESS(STL)and iTransformer model optimized by improved arithmetic optimization algorithm(IAOA).First,to fully extract the power data features,STL is used to decompose the original data into components with less redundant *** extracted components as well as the weather data are then input into iTransformer for short-term wind power *** final predicted short-term wind power curve is obtained by combining the predicted *** improve the model accuracy,IAOA is employed to optimize the hyperparameters of *** proposed approach is validated using real-generation data from different seasons and different power stations inNorthwest China,and ablation experiments have been ***,to validate the superiority of the proposed approach under different wind characteristics,real power generation data fromsouthwestChina are utilized for *** results with the other six state-of-the-art prediction models in experiments show that the proposed model well fits the true value of generation series and achieves high prediction accuracy.

关键词： Short-termwind power forecast improved arithmetic optimization algorithm iTransformer algorithm SimuNPS

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Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

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Computer Modeling in engineering & Sciences 2025年第1期142卷 579-607页

作者： Pongsakon Promsawat Weerapan Sae-dan Marisa Kaewsuwan Weerawat Sudsutad Aphirak Aphithana department of Civil engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand department of Computer engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand department of Statistics Faculty of ScienceRamkhamkaeng UniversityBangkok10240Thailand

The ability to accurately predict urban traffic flows is crucial for optimising city ***,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility *** learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal ***,these models often become overly complex due to the large number of hyper-parameters *** this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction *** comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest *** the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 ***,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer *** Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time *** numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

关键词： Graph neural networks convolutional neural network deep learning dynamic multi-graph spatio-temporal

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Advancing depth perception in spatial computing with binocular metalenses

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Opto-Electronic Advances 2025年第1期8卷 1-3页

作者： Junkyeong Park Gyeongtae Kim Junsuk Rho department of Mechanical engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea department of Chemical engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea department of electrical engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea POSCO-POSTECH-RIST Convergence Research Center for Flat Optics and Metaphotonics Pohang 37673Republic of Korea

Spatial computing and augmented reality are advancing rapidly,with the goal of seamlessly blending virtual and physical ***,traditional depth-sensing systems are bulky and energy-intensive,limiting their use in wearable *** overcome this,recent research by *** et *** a compact binocular metalens-based depth perception system that integrates efficient edge detection through an advanced neural *** system enables accurate,realtime depth mapping even in complex environments,enhancing potential applications in augmented reality,robotics,and autonomous systems.

关键词： metasurface metalens deep learning depth perception edge detection

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Undrained bearing capacity of obliquely-eccentrically loaded shallow foundations overlying a heterogeneous and inherently anisotropic clay deposit

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Journal of Rock Mechanics and Geotechnical engineering 2025年第1期17卷 586-613页

作者： Maedeh Nasiri Pishvari Hessam Fathipour Suraparb Keawsawasvong Boonchai Ukritchon Meghdad Payan Reza Jamshidi Chenari department of Civil engineering Faculty of EngineeringUniversity of GuilanRashtIran Research Unit in Sciences and Innovative Technologies for Civil engineering Infrastructures Department of Civil EngineeringThammasat School of EngineeringThammasat UniversityThailand department of Civil engineering.Chulalongkorn University BangkokThailand department of Civil engineering GeoEngineering Centre at Queen's RMCRoyal Military College of CanadaKingstonCanada

Clay deposits typically exhibit significant degrees of heterogeneity and anisotropy in their strength and stiffness *** non-monotonic responses can significantly impact the stability analysis and design of overlying shallow *** this study,the undrained bearing capacity of shallow foundations resting on inhomogeneous and anisotropic clay layers subjected to oblique-eccentric combined loading is investigated through a comprehensive series of finite element limit analysis(FELA)based on the well-established lower-bound theorem and second-order cone programming(SOCP).The heterogeneity of normally consolidated(NC)clays is simulated by adopting a well-known general model of undrained shear strength increasing linearly with *** contrast,for overconsolidated(OC)clays,the variation of undrained shear strength with depth is considered to follow a bilinear ***,the inherent anisotropy is accounted for by adopting different values of undrained shear strength along different directions within the soil medium,employing an iterative-based *** results of numerical simulations are utilized to investigate the influences of natural soil heterogeneity and inherent anisotropy on the ultimate bearing capacity,failure envelope,and failure mechanism of shallow foundations subjected to the various combinations of vertical-horizontal(V-H)and vertical-moment(V-M)loads.

关键词： Shallow foundation Bearing capacity Combined loading Undrained shear strength Inherent anisotropy Heterogeneity

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Analysis of Nuclear Structure Properties and Stellar β-decay Rates of Even–Even 106–120Zr Isotopes

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Research in Astronomy and Astrophysics 2025年第1期25卷 162-174页

作者： Abdul Kabir Jameel-Un Nabi Syeda Anmol Rida Izzah Anwaar Noor-Ul Ain Raza Hamad Almujibah department of Space Science Institute of Space Technology University of Wah department of Civil engineering College of EngineeringTaif University

The nuclear ground state properties of even–even106–120Zr nuclei have been investigated within the framework of the relativistic mean field （RMF） *** RMF model with density-dependent DDME2 and DDPC1interactions is utilized for the calculation of potential energy curves,the nuclear ground-state deformation parameters （β2）,neutron separation energies (S_nand S2n) and neutron skin thickness (rnp) of selected Zr ***,the β-decay properties of Zr isotopes were studied using the proton-neutron quasi-particle random phase approximation （pn-QRPA） *** include Gamow–Teller strength distributions,β-decay half-lives and stellar electron emission/positron capture *** β2values computed from the RMF model were employed in the pn-QRPA model as an input parameter for the calculations of β-decay properties for even–even106–120Zr *** stellar rates were computed using the pn-QRPA framework with three different types of deformation *** at high temperature （T9≥2） and low density (ρYe≤10～7g cm-3) values,the sum of electron emission and positron capture rates has a sizeable contribution （with positive exponents） to the stellar rates.

关键词： (stars:) supernovae: individual (r-process) abundances astroparticle physics elementary particles nuclear reactions nucleosynthesis

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Heterogeneously integrated silicon-conductive oxide MOSCAP microring modulator array

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Photonics Research 2025年第1期13卷 187-193页

作者： WEI-CHE HSU SAEED ABDOLHOSSEINI HAISHENG RONG RANJEET KUMAR BERND ZECHMANN ALAN X.WANG department of electrical and Computer engineering Baylor University School of electrical engineering and Computer Science Oregon State University Intel Corporation Center of Microscopy and Imaging Baylor University

In pursuit of energy-efficient optical interconnect, the silicon microring modulator（Si-MRM） has emerged as a pivotal device offering an ultra-compact footprint and capability of on-chip wavelength division multiplexing（WDM）. This paper presents a 1 × 4 metal-oxide-semiconductor capacitor（MOSCAP） Si-MRM array gated by high-mobility titanium-doped indium oxide（ITi O）, which was fabricated by combining Intel's high-volume manufacturing process and the transparent conductive oxide（TCO） patterning with the university facility. The 1 × 4 Si-MRM array exhibits a high electro-optic（E-O） efficiency with Vπ· L of 0.12 V · cm and achieves a modulation rate of（3 × 25 + 1 × 15） Gb/s with a measured bandwidth of 14 GHz. Additionally, it can perform on-chip WDM modulation at four equally spaced wavelengths without using thermal heaters. The process compatibility between silicon photonics and TCO materials is verified by such an industry-university co-fabrication approach for the MOSCAP Si-MRM array and demonstrated enhanced performance from heterogeneous integration.

关键词： Modulation Optical interconnects Optical signals Silicon modulators Silicon photonics Wavelength division multiplexing

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The Electric Vehicle Surge:Effective Solutions for Charging Challenges with Advanced Converter Technologies

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Energy engineering 2025年第2期122卷 431-469页

作者： Rajanand Patnaik Narasipuram Md M.Pasha Saleha Tabassum Amit Singh Tandon Sustainability Group Cyient Ltd.Pune411057India department of Electronics and Communication engineering K.S.R.M.College of EngineeringKadapa516003India department of electrical and Electronics engineering K.S.R.M.College of EngineeringKadapa516003India Mobility Group Eaton India Innovation Center LLPPune411028India

The global adoption of Electric Vehicles(EVs)is on the rise due to their advanced features,with projections indicating they will soon dominate the private vehicle ***,improper management of EV charging can lead to significant *** paper reviews the development of high-power,reliable charging solutions by examining the converter topologies used in rectifiers and converters that transfer electricity from the grid to EV *** covers technical details,ongoing developments,and challenges related to these topologies and control *** integration of rapid charging stations has introduced various Power Quality(PQ)issues,such as voltage fluctuations,harmonic distortion,and supra-harmonics,which are discussed in *** paper also highlights the benefits of controlled EV charging and discharging,including voltage and frequency regulation,reactive power compensation,and improved power *** energy management and control strategies are crucial for optimizing EV battery charging within microgrids to meet increasing *** stations must adhere to specific converter topologies,control strategies,and industry standards to function *** paper explores microgrid architectures and control strategies that integrate EVs,energy storage units(ESUs),and Renewable Energy Sources(RES)to enhance performance at charging *** emphasizes the importance of various RES-connected architectures and the latest power converter ***,the paper provides a comparative analysis of microgrid-based charging station architectures,focusing on energy management,control strategies,and charging converter *** goal is to offer insights into future research directions in EV charging systems,including architectural considerations,control factors,and their respective advantages and disadvantages.

关键词： Electric vehicles converters rectifiers power and voltage levels efficiency supra-harmonics

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Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

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Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Zhongyue Zou Xuesong Mei State Key Laboratory for Manufacturing Systems engineering Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina Shaanxi Key Laboratory of Intelligent Robots School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049ShaanxiChina department of electrical engineering and Automation Luoyang Institute of Science and TechnologyLuoyang 471023HenanChina School of Mechanical engineering Hangzhou Dianzi UniversityHangzhou 310018ZhejiangChina

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Lithium-ion battery State-of-health estimation Data-driven Machine learning Ensemble learning Ensemble diversity

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A Two-Pronged Approach to Security of Discrete-Event Systems

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Journal of Systems Science & Complexity 2025年第01期 178-209页

作者： MATSUI Shoma RUDIE Karen CAI Kai department of electrical and Computer engineering & the Ingenuity Labs Research Institute Queen's University department of Core Informatics Osaka Metropolitan University

This paper investigates a security problem of simultaneously addressing two types of attacks: Eavesdropping and infiltration. The authors model the target system as a discrete-event system(DES) with subsets of concealable events and protectable events, in order to make the proposed methodology applicable to various practical systems and employ two existing works of DES security: Degree of opacity and state protection. Specifically, the authors consider that all protectable events are observable, and some observable events are concealable. In addition, protectable events cannot be protected once they are concealed. Given such a constraint, the goal is to figure out which events to conceal and which transitions to protect so that the prescribed requirements of degree of opacity and state protection are satisfied. In this work the authors decide which events to conceal as all transitions of a given event label are concealed or not concealed. The proposed problem formulation also requires a solution to only involve absolutely necessary protectable events in order for the system to avoid superfluous protection costs. The authors first examine a general version of our security problem with an intuitive algorithm to compute acceptable solutions, and then present a special version which results in a reduced computation time compared to the general version.

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Effects of bidirectional interaction on inelastic seismic response:When is its effect significant?

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Earthquake engineering and engineering Vibration 2025年第1期24卷 113-134页

作者： Atanu Santra Rana Roy department of Aerospace engineering and Applied Mechanics Indian Institute of Engineering Science and TechnologyShibpur 711103India

Motivated by the early works on bidirectional interaction and the breakthrough to estimate seismic response to bidirectional shaking via unidirectional analysis,it is essential to answer the question:When is the interaction effect significant?Early works concluded that the effect of interaction is pronounced for stiff systems;consequently,the straightforward method for estimating seismic response to bidirectional excitation by using unidirectional analyses is verified primarily for short period ***,it is essential to identify the domain of significance for bidirectional interaction before adopting this simple methodology in *** parametrically defined systems with elastoplastic and degrading hysteresis models are studied under near-fault motions,assuming strength-independent and strength-dependent *** force-based and displacement-based analyses,conducted in parallel,reveal that the interaction effect is considerable for stiff systems,especially with degrading characteristics in a relatively low inelasticity ***,the bidirectional effect may be significant even for highly flexible systems,especially for residual deformation,which in earlier works was *** range of significance depends on the hysteresis model,system parameters,and response *** analysis is carried out with the results of the case studies,and the derived regression models may be used for a preliminary assessment of the impact of interaction in advance.

关键词： bidirectional residual forward-directive fling force-based displacement-based regression

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