检索结果-南通市图书馆

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

在线全文

学校读者我要写书评

暂无评论

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 University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University Department of Electrical Engineering and Automation Luoyang Institute of Science and Technology School of Mechanical Engineering Hangzhou Dianzi University

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： Contrastive Learning

Possible PKHD1 Hot-spot Mutations Related to Early Kidney Function Failure or Hepatofibrosis in Chinese Children with ARPKD:A Retrospective Single Center Cohort Study and Literature Review

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Current Medical Science 2020年第5期40卷 835-844页

作者： Li-ru QIU rong-rong xu Jin-hui TANG Jian-hua ZHOU Department of Pediatrics Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030China

PKHD1 mutations are generally considered to cause autosomal recessive polycystic kidney disease(ARPKD).ARPKD is a rare disorder and one o f the most severe conditions leading to end-stage renal disease in *** the biallelic deletion mutation,patients have difficulty in surviving the perinatal period,resulting in perinatal or neonatal *** study retrospectively analyzed patient characteristics,imaging characteristics,laboratory examinations and family surveys from 7 Chinese children with different PKHD1 gene mutations diagnosed by high-throughput sequencing from January 2014 to February 2018.O f the 7 children,there were 3 males and 4 *** missense mutations,two frameshift mutations,two deletion mutations,and two intronic slicing mutations were *** of the mutations have not previously been *** the literature search,we identified a total of 29 Chinese children with PKHD1 *** missense mutation c.2507T>C in exon 24 was found in one patient in our study,and five patients with liver fibrosis but normal renal function were reported in the *** missense mutation c.5935G>A in exon 37 was found in two patients in our study and three cases in the *** patients had renal failure at an age as young as 1 year of those five patients with the missense mutation c.5935G>A in exon *** was concluded that:(1)Kidney length more than 2-3 SDs above the mean and early-onset hypertension might be associated with PKHDI-associated ARPICD;(2)The more enlarged the kidney size is,the lower the renal function is likely to be;(3)c.5935G>A may be a hot spot that leads to early renal failure in Chinese children with PKHD1 mutations;(4)c.2507T>C may be a hot-spot mutation associated with hepatic lesions in Chinese children with PKHD1.

关键词： PKHD1 mutations autosomal recessive polycystic kidney disease clinical phenotype genotypic characteristics Chinese children

Co-occurrence prediction in a large location-based social network

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Computer Science 2013年第2期7卷 185-194页

作者： rong-hua LI Jianquan LIU Jeffrey xu YU Hanxiong CHEN Hiroyuki KITAGAWA Department of System Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong China Faculty of Engineering Information and systems University of TsukubaJapan Ibaraki 305-8577 Cloud System Research Laboratories NEC CorporationJapan Tokyo 108-8001

Location-based social network （LBSN） is at the forefront of emerging trends in social network services （SNS） since the users in LBSN are allowed to ＂check-in＂ the places （locations） when they visit them. The accurate geographi- cal and temporal information of these check-in actions are provided by the end-user GPS-enabled mobile devices, and recorded by the LBSN system. In this paper, we analyze and mine a big LBSN data, Gowalla, collected by us. First, we investigate the relationship between the spatio-temporal co- occurrences and social ties, and the results show that the co- occurrences are strongly correlative with the social ties. Sec- ond, we present a study of predicting two users whether or not they will meet （co-occur） at a place in a given future time, by exploring their check-in habits. In particular, we first intro- duce two new concepts, bag-of-location and bag-of-time-lag, to characterize user＇s check-in habits. Based on such bag rep- resentations, we define a similarity metric called habits sim- ilarity to measure the similarity between two users＇ check-in habits. Then we propose a machine !earning formula for pre- dicting co-occurrence based on the social ties and habits sim- ilarities. Finally, we conduct extensive experiments on our dataset, and the results demonstrate the effectiveness of the proposed method.

关键词： location-based social networks Gowalla co-occurrence

Targets capture by distributed active swarms via bio-inspired reinforcement learning

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun xu Yue Li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang Bo Li Institute of Biomechanics and Medical Engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University Institute of Nuclear and New Energy Technology Tsinghua University Shanghai Aerospace Control Technology Institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

Design and implementation of reconfigurable CNN accelerator architecture based on elastic storage

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

The Journal of China Universities of Posts and Telecommunications 2025年

作者： Shan Rui xu Jianing Huo Ziqing College of Electronic Engineering， Xi'an University of Post and Telecommunications

With the rapid iteration of neural network algorithms， higher requirements was placed on the computational performance and memory access bandwidth of neural network accelerators. Simply increasing bandwidth cannot improve energy efficiency， so improving data reuse rate is a hot research topic. From the perspective of supporting data reuse， a reconfigurable convolutional neural networks (CNN) accelerator based on elastic storage was designed in this paper. By supporting elastic memory access and flexible data flow， it reduces data movement between the processor and memory， eases the bandwidth pressure and enhances CNN acceleration performance. The experimental results indicate that conducting 1×1 convolution and 3×3 convolution when performing convolution calculations， the execution speed increased by 25.00% and 61.61%， respectively. The 3×3 maximum pooling speed was increased by 76.04%.

关键词：

Copper catalyzed borylative cyclization of 3-arylallyl carbamoyl chloride with B_(2)pin_(2):stereoselective synthesis of cis-2-aryl-3-boryl-γ-lactams

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Chemical Letters 2021年第7期32卷 2297-2300页

作者： Mei-hua Shen Ting-Biao Wan Xiu-rong huang Yan Li Dan-hua Qian hua-Dong xu Defeng xu Jiangsu Key Laboratory of Advanced Catalytic Materials&Technology School of PharmacyChangzhou UniversityChangzhou 213164China

Borylative cyclization of E-3-arylallyl carbamoyl chlorides is achieved through copper catalyzed intramolecular carboboration with B_(2)pin_(2).2-Aryl-3-boryl-γ-lactams are formed with exclusive ***-Dppp combination ... 详细信息

关键词： Carboboration Borylative cyclization Copper catalysis Allyl carbamoyl chloride Borocupration γ-Lactam

Enantioselective β-alkenylation of α,β-unsaturated aldehydes via chiral biphosphine ligand modified dirhodium(II) catalysis

在线全文

学校读者我要写书评

暂无评论

Science China Chemistry 2025年

作者： Guangli xu Hongda Chen Xiaoming Wang State Key Laboratory of Organometallic Chemistry and Shanghai Hongkong Joint Laboratory in Chemical Synthesis Center for Excellence in Molecular Synthesis Shanghai Institute of Organic Chemistry University of Chinese Academy of Sciences Chinese Academy of Sciences School of Chemistry and Materials Science Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences School of Chemistry and Chemical Engineering Henan Normal University

Dirhodium(II) complexes have achieved great success in organic synthesis,and fine-tuning their catalytic properties with various bridging ligands is well-investigated in carbene ***,combining dirhodium(II) with a sophisticated ligand as a catalyst in other reactions is still extremely challenging,especially for the asymmetric synthesis of valuable chiral ***,we report a dirhodium(II)/(S)-MeO-BIPHEP catalytic system for the challenging asymmetric β-alkenylation of α,β-unsaturated aldehydes,affording the corresponding chiral conjugate addition products in good yields with high enantioselectivities.A couple of drug-derived substrates were also compatible with the protocol,which has been successfully used to prepare biologically relevant pyranochromene *** mechanistic studies suggested that the dirhodium core might remain intact over the catalytic cycle,and the chiral diphosphine ligand plays a key role in this novel reactivity and determining the high enantioselectivities of the asymmetric conjugate addition.

关键词：

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

电沉积法制备镍-纳米碳复合镀层及其工艺

上海大学学报（自然科学版） 2004年第3期10卷 296-301页

作者：桑付明成旦红曹铁华袁蓉徐伟一上海大学理学院上海200436

该文讨论了镍纳米碳复合共沉积中纳米碳含量、温度、电流密度、表面活性剂、搅拌等因素对纳米碳微粒共沉积量的影响.总结了镍纳米碳复合镀层的制备方法,并对镍纳米碳的共沉积机理作了探讨.

关键词：镍-纳米碳共沉积复合镀层

Inspires effective alternatives to backpropagation:predictive coding helps understand and build learning

在线全文

学校读者我要写书评

暂无评论

Neural Regeneration Research 2025年第11期20卷 3215-3216页

作者： Zhenghua xu Miao Yu Yuhang Song School of Health Sciences and Biomedical Engineering Hebei University of TechnologyTianjinChina Department of Computer Science University of OxfordOxfordUK

Artificial neural networks are capable of machine learning by simulating the hiera rchical structure of the human *** enable learning by brain and machine,it is essential to accurately identify and correct the prediction errors,referred to as credit assignment(Lillicrap et al.,2020).It is critical to develop artificial intelligence by understanding how the brain deals with credit assignment in neuroscience.

关键词： assignment learning enable