MULTI-MODEL

作品数：90被引量：223H指数：8
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AI-Powered Threat Detection in Online Communities: A Multi-Modal Deep Learning Approach
《Journal of Computer and Communications》2025年第2期155-171,共17页Ravi Teja Potla 
The fast increase of online communities has brought about an increase in cyber threats inclusive of cyberbullying, hate speech, misinformation, and online harassment, making content moderation a pressing necessity. Tr...
关键词：Multi-Model AI Deep Learning Natural Language Processing (NLP) Explainable AI (XI) Federated Learning Cyber Threat Detection LSTM CNNS 
Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives
《Journal of Energy Chemistry》2025年第1期739-759,共21页Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Zhongyue Zou Xuesong Mei 
National Natural Science Foundation of China (52075420);Fundamental Research Funds for the Central Universities (xzy022023049);National Key Research and Development Program of China (2023YFB3408600)。
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 per...
关键词：Lithium-ion battery State-of-health estimation DATA-DRIVEN Machine learning Ensemble learning Ensemble diversity 
Trends and multi-model prediction of hepatitis B incidence in Xiamen被引量：1
《Infectious Disease Modelling》2024年第4期1276-1288,共13页Ruixin Zhang Hongfei Mi Tingjuan He Shuhao Ren Renyan Zhang Liansheng Xu Mingzhai Wang Chenghao Su 
funded by Xiamen Medical and Health Key Project[grant numbers 3502Z20191105].
Background:This study aims to analyze the trend of Hepatitis B incidence in Xiamen City from 2004 to 2022,and to select the best-performing model for predicting the number of Hepatitis B cases from 2023 to 2027.Method...
关键词：Hepatitis B Temporal trends PREDICTION Joinpoint regression model Age-period-cohort model Neural network autoregressive model 
Deciphering Car Crash Dynamics in Greater Melbourne:a Multi-Model Machine Learning and Geospatial Analysis
《Journal of Geodesy and Geoinformation Science》2024年第4期36-55,共20页Christopher JOHNSON ZHOU Heng Richard TAY SUN Qian(Chayn) 
Linking Health,Place and Urban Planning through the Australian Urban Observatory by Ian Potter Foundation,Australia.
In the continually evolving landscape of data-driven methodologies addressing car crash patterns,a holistic analysis remains critical to decode the complex nuances of this phenomenon.This study bridges this knowledge ...
关键词：car crash dynamics hexagonalization multi-model machine learning spatial planning intervention 
Artificial Intelligence Enabled Future Wireless Electric Vehicles with Multi-Model Learning and Decision Making Models
《Tsinghua Science and Technology》2024年第6期1776-1784,共9页Gajula Ramesh Anil Kumar Budati Shayla Islam Louai A.Maghrabi Abdullah Al-Atwai 
the Ministry of Higher Education Malaysia for funding this research project through Fundamental Research Grant Scheme(FRGS)(No.FRGS/1/2022/TK02/UCSI/02/1)and also to UCSI University,Malaysia.
In the contemporary era,driverless vehicles are a reality due to the proliferation of distributed technologies,sensing technologies,and Machine to Machine(M2M)communications.However,the emergence of deep learning tech...
关键词：wireless vehicles deep learning multi-model learning reinforcement learning Artificial Intelligence(Al) 
Harnessing Distributed Deep Learning for Landslide Displacement Prediction:A Multi-Model Collaborative Approach Amidst Data Silos
《Journal of Earth Science》2024年第5期1770-1775,共6页Bingchen Li Changdong Li Yong Liu Jie Tan Pengfei Feng Wenmin Yao 
supported by the National Natural Science Foundation of China(Nos.42090054,42207179,42107181);the China Postdoctoral Science Foundation(No.2021M702932);the Hubei Provincial Natural Science Foundation of China(No.2022CFB801)。
0 INTRODUCTION Timely and accurate prediction of landslide displacement is crucial for the early warning of landslide disasters(Tang et al.,2019;Zhao et al.,2019;Zhou et al.,2018).Among various landslide displacement ...
关键词：LANDSLIDE PREDICTION LANDSLIDE 
Identification of working conditions and prediction of FeO content in sintering process of iron ore fines被引量：1
《Journal of Iron and Steel Research International》2024年第9期2090-2100,共11页Xiao-ming Li Bao-rong Wang Zhi-heng Yu Xiang-dong Xing 
the National Natural Science Foundation of China(52174325);the Key Research and Development Program of Shaanxi(Grant Nos.2020GY-166 and 2020GY-247);the Shaanxi Provincial Innovation Capacity Support Plan(Grant No.2023-CX-TD-53).
The iron oxide(FeO)content had a significant impact on both the metallurgical properties of sintered ores and the economic indicators of the sintering process.Precisely predicting FeO content possessed substantial pot...
关键词：Iron ore sintering Condition identification FeO prediction Multi-model integrated prediction model Feature engineering 
Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis被引量：1
《Journal of Biomedical Research》2024年第4期397-412,共16页Jiaqi Tang Lin Luo Bakwatanisa Bosco Ning Li Bin Huang Rongrong Wu Zihan Lin Ming Hong Wenjie Liu Lingxiang Wu Wei Wu Mengyan Zhu Quanzhong Liu Peng Xia Miao Yu Diru Yao Sali Lv Ruohan Zhang Wentao Liu Qianghu Wang Kening Li 
supported by the National Natural Science Foundation of China(Grant Nos.32200590 to K.L.,81972358 to Q.W.,91959113 to Q.W.,and 82372897 to Q.W.);the Natural Science Foundation of Jiangsu Province(Grant No.BK20210530 to K.L.).
Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been s...
关键词：acute myeloid leukemia cell surface markers PROGNOSIS drug sensitivity multi-model analysis 
MART(Splitting-Merging Assisted Reliable)Independent Component Analysis for Extracting Accurate Brain Functional Networks
《Neuroscience Bulletin》2024年第7期905-920,共16页Xingyu He Vince D.Calhoun Yuhui Du 
supported by the National Natural Science Foundation of China(62076157 and 61703253);the Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province(20210033);the National Institutes of Health(R01MH123610 and R01EB006841).
Functional networks(FNs)hold significant promise in understanding brain function.Independent component analysis(ICA)has been applied in estimating FNs from functional magnetic resonance imaging(fMRI).However,determini...
关键词：Independent component analysis Functional magnetic resonance imaging-Brain functional networks Clustering Multi-model-order 
Efficient and Secure IoT Based Smart Home Automation Using Multi-Model Learning and Blockchain Technology被引量：1
《Computer Modeling in Engineering & Sciences》2024年第6期3387-3415,共29页Nazik Alturki Raed Alharthi Muhammad Umer Oumaima Saidani Amal Alshardan Reemah M.Alhebshi Shtwai Alsubai Ali Kashif Bashir 
funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2024R333);Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the d...
关键词：Blockchain Internet of Things(IoT) smart home automation CYBERSECURITY 
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