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Wavelet Transform Convolution and Transformer-Based Learning Approach for Wind Power Prediction in Extreme Scenarios
《Computer Modeling in Engineering & Sciences》2025年第4期945-965,共21页Jifeng Liang Qiang Wang Leibao Wang Ziwei Zhang Yonghui Sun Hongzhu Tao Xiaofei Li 
funded by the Science and Technology Project of State Grid Corporation of China under Grant No.5108-202218280A-2-299-XG.
Wind power generation is subjected to complex and variable meteorological conditions,resulting in intermittent and volatile power generation.Accurate wind power prediction plays a crucial role in enabling the power gr...
关键词：Extreme scenarios conditional generative adversarial network wavelet transform Transformer wind power prediction 
DaC-GANSAEBF:Divide and Conquer-Generative Adversarial Network-Squeeze and Excitation-Based Framework for Spam Email Identification
《Computer Modeling in Engineering & Sciences》2025年第3期3181-3212,共32页Tawfeeq Shawly Ahmed A.Alsheikhy Yahia Said Shaaban M.Shaaban Husam Lahza Aws I.Abu Eid Abdulrahman Alzahrani 
funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,Saudi Arabia under Grant No.(GPIP:71-829-2024).
Email communication plays a crucial role in both personal and professional contexts;however,it is frequently compromised by the ongoing challenge of spam,which detracts from productivity and introduces considerable se...
关键词：Email spam fraud light dual attention squeeze and excitation divide and conquer-generative adversarial network-squeeze and excitation-based framework security 
Unlocking the Potential:A Comprehensive Systematic Review of ChatGPT in Natural Language Processing Tasks
《Computer Modeling in Engineering & Sciences》2024年第10期43-85,共43页Ebtesam Ahmad Alomari 
As Natural Language Processing(NLP)continues to advance,driven by the emergence of sophisticated large language models such as ChatGPT,there has been a notable growth in research activity.This rapid uptake reflects in...
关键词：Generative AI large languagemodel(LLM) natural language processing(NLP) ChatGPT GPT(generative pretraining transformer) GPT-4 sentiment analysis NER information extraction ANNOTATION text classification 
Quantifying Uncertainty in Dielectric Solids’ Mechanical Properties Using Isogeometric Analysis and Conditional Generative Adversarial Networks
《Computer Modeling in Engineering & Sciences》2024年第9期2587-2611,共25页Shuai Li Xiaodong Zhao Jinghu Zhou Xiyue Wang 
Accurate quantification of the uncertainty in the mechanical characteristics of dielectric solids is crucial for advancing their application in high-precision technological domains,necessitating the development of rob...
关键词：Dielectric solid isogeometric finite element method surrogate model generative adversarial 
Conditional Generative Adversarial Network Enabled Localized Stress Recovery of Periodic Composites
《Computer Modeling in Engineering & Sciences》2024年第7期957-974,共18页Chengkan Xu Xiaofei Wang Yixuan Li Guannan Wang He Zhang 
the support from the National Key R&D Program of China underGrant(Grant No.2020YFA0711700);the National Natural Science Foundation of China(Grant Nos.52122801,11925206,51978609,U22A20254,and U23A20659);G.W.is supported by the National Natural Science Foundation of China(Nos.12002303,12192210 and 12192214).
Structural damage in heterogeneousmaterials typically originates frommicrostructures where stress concentration occurs.Therefore,evaluating the magnitude and location of localized stress distributions within microstru...
关键词：Periodic composites localized stress recovery conditional generative adversarial network 
Generative Multi-Modal Mutual Enhancement Video Semantic Communications
《Computer Modeling in Engineering & Sciences》2024年第6期2985-3009,共25页Yuanle Chen Haobo Wang Chunyu Liu Linyi Wang Jiaxin Liu Wei Wu 
supported by the National Key Research and Development Project under Grant 2020YFB1807602;Key Program of Marine Economy Development Special Foundation of Department of Natural Resources of Guangdong Province(GDNRC[2023]24);the National Natural Science Foundation of China under Grant 62271267.
Recently,there have been significant advancements in the study of semantic communication in single-modal scenarios.However,the ability to process information in multi-modal environments remains limited.Inspired by the...
关键词：Generative adversarial networks multi-modal mutual enhancement video semantic transmission deep learning 
Toward Improved Accuracy in Quasi-Static Elastography Using Deep Learning
《Computer Modeling in Engineering & Sciences》2024年第4期911-935,共25页Yue Mei Jianwei Deng Dongmei Zhao Changjiang Xiao Tianhang Wang Li Dong Xuefeng Zhu 
National Natural Science Foundation of China (12002075);National Key Research and Development Project (2021YFB3300601);Natural Science Foundation of Liaoning Province in China (2021-MS-128).
Elastography is a non-invasive medical imaging technique to map the spatial variation of elastic properties of soft tissues.The quality of reconstruction results in elastography is highly sensitive to the noise induce...
关键词：Nonhomogeneous elastic property distribution reconstruction deep learning finite element method inverse problem ELASTOGRAPHY conditional generative adversarial network 
Brain Functional Network Generation Using Distribution-Regularized Adversarial Graph Autoencoder with Transformer for Dementia Diagnosis被引量：1
《Computer Modeling in Engineering & Sciences》2023年第12期2129-2147,共19页Qiankun Zuo Junhua Hu Yudong Zhang Junren Pan Changhong Jing Xuhang Chen Xiaobo Meng Jin Hong 
This paper is partially supported by the British Heart Foundation Accelerator Award,UK(AA\18\3\34220);Royal Society International Exchanges Cost Share Award,UK(RP202G0230);Hope Foundation for Cancer Research,UK(RM60G0680);Medical Research Council Confidence in Concept Award,UK(MC_PC_17171);Sino-UK Industrial Fund,UK(RP202G0289);Global Challenges Research Fund(GCRF),UK(P202PF11);LIAS Pioneering Partnerships Award,UK(P202ED10);Data Science Enhancement Fund,UK(P202RE237);Fight for Sight,UK(24NN201);Sino-UK Education Fund,UK(OP202006);Biotechnology and Biological Sciences Research Council,UK(RM32G0178B8);LIAS Seed Corn,UK(P202RE969).
The topological connectivity information derived from the brain functional network can bring new insights for diagnosing and analyzing dementia disorders.The brain functional network is suitable to bridge the correlat...
关键词：Adversarial graph encoder label distribution generative transformer functional brain connectivity graph convolutional network DEMENTIA 
Single Image Desnow Based on Vision Transformer and Conditional Generative Adversarial Network for Internet of Vehicles被引量：1
《Computer Modeling in Engineering & Sciences》2023年第11期1975-1988,共14页Bingcai Wei Di Wang Zhuang Wang Liye Zhang 
supported by School of Computer Science and Technology,Shandong University of Technology.This paper is supported by Shandong Provincial Natural Science Foundation,China(Grant Number ZR2019BF022);National Natural Science Foundation of China(Grant Number 62001272).
With the increasing popularity of artificial intelligence applications,machine learning is also playing an increasingly important role in the Internet of Things(IoT)and the Internet of Vehicles(IoV).As an essential pa...
关键词：Artificial intelligence Internet of Things vision transformer deep learning image desnow 
A Novel Motor Fault Diagnosis Method Based on Generative Adversarial Learning with Distribution Fusion of Discrete Working Conditions
《Computer Modeling in Engineering & Sciences》2023年第8期2017-2037,共21页Qixin Lan Binqiang Chen Bin Yao 
supported by the National Key Research and Development Program of China (No.2020YFB1713503);the Fundamental Research Funds for the Central Universities (No.20720190009);2019 Industry-University-Research Cooperation Project of Aero Engine Corporation of China (No.HFZL2019CXY02).
Many kinds of electrical equipment are used in civil and building engineering.The motor is one of the main power components of this electrical equipment,which can provide stable power output.During the long-term use o...
关键词：Motor fault diagnosis data augmentation wavelet decomposition generative adversarial network civil and building engineering 
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