检索结果-南通市图书馆

Structured Multi-Head Attention Stock Index Prediction Method Based Adaptive Public Opinion Sentiment Vector

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第1期78卷 1503-1523页

作者： Cheng Zhao Zhe Peng Xuefeng Lan Yuefeng Cen Zuxin Wang school of Economics Zhejiang University of TechnologyHangzhouChina College of management Zhejiang University of TechnologyHangzhouChina Informatization Office Zhejiang University of TechnologyHangzhouChina school of Information and Electronic Engineering Zhejiang University of Science&TechnologyHangzhouChina school of Economics and management Universiti Putra MalaysiaDaerah PetalingNegeri SelangorMalaysia

The present study examines the impact of short-term public opinion sentiment on the secondary market,with a focus on the potential for such sentiment to cause dramatic stock price fluctuations and increase investment *** quantification of investment sentiment indicators and the persistent analysis of their impact has been a complex and significant area of *** this paper,a structured multi-head attention stock index prediction method based adaptive public opinion sentiment vector is *** proposedmethod utilizes an innovative approach to transform numerous investor comments on social platforms over time into public opinion sentiment vectors expressing complex *** then analyzes the continuous impact of these vectors on the market through the use of aggregating techniques and public opinion data via a structured multi-head attention *** experimental results demonstrate that the public opinion sentiment vector can provide more comprehensive feedback on market sentiment than traditional sentiment polarity ***,the multi-head attention mechanism is shown to improve prediction accuracy through attention convergence on each type of input information *** absolute percentage error(MAPE)of the proposedmethod is 0.463%,a reduction of 0.294% compared to the benchmark attention ***,the market backtesting results indicate that the return was 24.560%,an improvement of 8.202% compared to the benchmark *** results suggest that themarket trading strategy based on thismethod has the potential to improve trading profits.

关键词： Public opinion sentiment structured multi-head attention stock index prediction deep learning

TransTM:A device-free method based on time-streaming multiscale transformer for human activity recognition

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Defence Technology（防务技术） 2024年第2期32卷 619-628页

作者： Yi Liu Weiqing Huang Shang Jiang Bobai Zhao Shuai Wang Siye Wang Yanfang Zhang Institute of Information Engineering Chinese Academy of Sciences School of Cyber SecurityUniversity of Chinese Academy of SciencesBeijingChina school of Information management Beijing Information Science and Technology UniversityBeijingChina

RFID-based human activity recognition(HAR)attracts attention due to its convenience,noninvasiveness,and privacy *** RFID-based HAR methods use modeling,CNN,or LSTM to extract features ***,they have shortcomings:1)requiring complex hand-crafted data cleaning processes and 2)only addressing single-person activity recognition based on specific RF *** solve these problems,this paper proposes a novel device-free method based on Time-streaming Multiscale Transformer called *** model leverages the Transformer's powerful data fitting capabilities to take raw RFID RSSI data as input without ***,we propose a multiscale convolutional hybrid Transformer to capture behavioral features that recognizes singlehuman activities and human-to-human *** with existing CNN-and LSTM-based methods,the Transformer-based method has more data fitting power,generalization,and ***,using RF signals,our method achieves an excellent classification effect on human behaviorbased classification *** results on the actual RFID datasets show that this model achieves a high average recognition accuracy(99.1%).The dataset we collected for detecting RFID-based indoor human activities will be published.

关键词： Human activity recognition RFID Transformer

维普期刊数据库

Advanced Algorithm for Parameters Estimation of Negative Binomial Distribution with High Dimensional Sparse Group Structure

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Science & Complexity 2024年第5期37卷 2173-2195页

作者： LI Meiqi JIN Baisuo school of management University of Science and Technology of China

Negative binomial regression is a powerful technique for modeling count data, particularly when dealing with overdispersion. However, estimating the parameters for large-dimensional sparse models is challenging due to the complexity of optimizing the mean and dispersion parameter of the negative binomial distribution. To address this issue, the authors propose a novel approach that employs two iterations of the majorize-minimize(MM) algorithm, one for estimating the dispersion parameter and the other for estimating the mean parameters. These approaches improve the convergence speed and stability of the algorithm. The authors also use group penalty for variable selection, which enhances the accuracy and efficiency of the algorithm. The proposed method provides an explicit solution,simplifies the iteration process, and maintains good stability while ensuring algorithm ***, the authors apply the proposed algorithm to the zero-inflated model and demonstrate its promising predictive performance on specific data sets. The research has important implications for count data modeling and analysis in various fields, such as data mining, machine learning, and bioinformatics.

关键词：

Provoking Buying Behaviors Amid Crises:Unfolding the Underlying Mechanisms of Psychological Impairments

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

International Journal of Mental Health Promotion 2024年第4期26卷 279-292页

作者： Muhammad Waleed Ayub Ghouri Guofeng Wang Muhammad Ali Hussain Zhisheng Li Tachia Chin school of management Zhejiang University of TechnologyHangzhou310023China school of management and Economics University of Electronic Science and Technology of ChinaChengdu611731China Business school NingboTech UniversityNingbo315100China

Crises in the past have caused devastating,long-lasting impacts on the global *** after-effects always bring some dynamic and rigorous challenges for businesses and *** challenges have always been a point of discussion for *** recent COVID-19 pandemic emaciated the global economy,leaving everyone mired in uncertainty,fear,and psychological *** of the headwind features utilized by consumers during pandemic was panic buying(PB),which must be explored in various contexts for policymakers and *** address this gap,this study deployed a moderated mediation mechanism,integrating the health belief model(HBM)and competitive arousal theory(CAT)to excavate the notions underlying PB with the intrusion of evolved real-time psychological disorders:intolerance of uncertainty(IU)and cyberchondria(CYC).The study was conducted as a natural experiment in a South Asian developing economy using online *** found that health beliefs—perceived severity(PSV)and perceived susceptibility(PSC)—positively impact perceived arousal(PA),which causes PB,and that PA has a sturdy mediator ***,in the relationship between health beliefs and arousal,the different psychological disorders were found to have significant moderating roles The study findings can help mitigate risk uncertainties and panic situations and thus contribute to consumers’wellbeing.

关键词： Panic buying health belief model mental health competitive arousal theory intolerance of uncertainty cyberchondria

Time for a change:Rethinking the global renewable energy transition from the Sustainable Development Goals and the Paris Climate Agreement

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

The Innovation 2024年第1期5卷 13-14页

作者： Guanglei Yang Donglan Zha Dongqin Cao Guoxing Zhang school of management Lanzhou UniversityLanzhou 730000China College of Economics and management Nanjing University of Aeronautics and AstronauticsNanjing 211106China school of Economics Lanzhou UniversityLanzhou 730000China

The concept of energy transition was initially proposed by the German Academy of Sciences in 1980,advocating for the abandonment of nuclear power and oil in response to the energy *** that time,insufficient attention was given to the energy *** 1980 to 1992,the global economy experienced significant growth,with the gross domestic product doubling from 11.34 trillion dollars to 25.41 trillion dollars(data from the World Bank).

关键词： Sustainable dollar transition

Do community responses influence OSS contributor retention? A survival analysis

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(Information Sciences) 2024年第8期67卷 331-333页

作者： Zhe WANG Zhixing LI Yue YU school of Public Policy and management Tsinghua University College of Computer National University of Defense Technology

Open source software(OSS) projects usually employ a community-based model, where geographically distributed developers from around the world collaborate online [1].With the rise of social coding sites like Git Hub, contributing to OSS projects has become easier and more accessible, motivating many developers to join the OSS community [2]. The continued submission of high-quality contributions from these community developers has led to numerous corrections, improvements, and innovations in many successful OSS projects [1, 2].

关键词：

Recursive filtering of multi-rate cyber-physical systems with unknown inputs under adaptive event-triggered mechanisms

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Information Technology & Electronic Engineering 2024年第2期25卷 250-259页

作者： Ying SUN Miaomiao FU Jingyang MAO Guoliang WEI Business school University of Shanghai for Science and TechnologyShanghai200093China Shanghai Caoyang Vocational school Shanghai200333China school of Electrical and Electronic Engineering Shanghai Institute of TechnologyShanghai201418China school of Intelligent Emergency management University of Shanghai for Science and TechnologyShanghai200093China

Cyber-physical systems(CPSs)take on the characteristics of both multiple rates of information collection and processing and the dependency on information *** purpose of this paper is to develop a joint recursive filtering scheme that estimates both unknown inputs and system states for multi-rate CPSs with unknown *** cyberspace,the information transmission between the local joint filter and the sensors is governed by an adaptive event-triggered ***,the desired parameters of joint filters are determined by a set of algebraic matrix equations in a recursive way,and a sufficient condition verifying the boundedness of filtering error covariance is found by resorting to some algebraic operation.A state fusion estimation scheme that uses local state estimation is proposed based on the covariance intersection(CI)based fusion ***,an illustrative example demonstrates the effectiveness of the proposed adaptive event-triggered recursive filtering algorithm.

关键词： Cyber-physical systems Multi-rate Joint recursive filtering Adaptive event-triggered mechanisms Unknown inputs

维普期刊数据库

A Degradation Type Adaptive and Deep CNN-Based Image Classification Model for Degraded Images

在线全文

学校读者我要写书评

暂无评论

工程与科学中的计算机建模(英文) 2024年第1期138卷 459-472页

作者： Huanhua Liu Wei Wang Hanyu Liu Shuheng Yi Yonghao Yu Xunwen Yao school of Information Technology and management Hunan University of Finance and EconomicsChangsha410205China

Deep Convolutional Neural Networks(CNNs)have achieved high accuracy in image classification tasks,however,most existing models are trained on high-quality images that are not subject to image *** practice,images are often affected by various types of degradation which can significantly impact the performance of *** this work,we investigate the influence of image degradation on three typical image classification CNNs and propose a Degradation Type Adaptive Image Classification Model(DTA-ICM)to improve the existing CNNs’classification accuracy on degraded *** proposed DTA-ICM comprises two key components:a Degradation Type Predictor(DTP)and a Degradation Type Specified Image Classifier(DTS-IC)set,which is trained on existing CNNs for specified types of *** DTP predicts the degradation type of a test image,and the corresponding DTS-IC is then selected to classify the *** evaluate the performance of both the proposed DTP and the DTA-ICMon the Caltech 101 *** experimental results demonstrate that the proposed DTP achieves an average accuracy of 99.70%.Moreover,the proposed DTA-ICM,based on AlexNet,VGG19,and ResNet152,exhibits an average accuracy improvement of 20.63%,18.22%,and 12.9%,respectively,compared with the original CNNs in classifying degraded *** suggests that the proposed DTA-ICM can effectively improve the classification performance of existing CNNs on degraded images,which has important practical implications.

关键词： Image recognition image degradation machine learning deep convolutional neural network

Performance evaluation of seven multi-label classification methods on real-world patent and publication datasets

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Data and Information Science 2024年第2期9卷 81-103页

作者： Shuo Xu Yuefu Zhang Xin An Sainan Pi College of Economics and management Beijing University of TechnologyBeijing 100124China school of Economics&management Beijing Forestry UniversityBeijing 100083China

Purpose:Many science,technology and innovation(STI)resources are attached with several different *** assign automatically the resulting labels to an interested instance,many approaches with good performance on the benchmark datasets have been proposed for multi-label classification task in the ***,several open-source tools implementing these approaches have also been ***,the characteristics of real-world multi-label patent and publication datasets are not completely in line with those of benchmark ***,the main purpose of this paper is to evaluate comprehensively seven multi-label classification methods on real-world *** limitations:Three real-world datasets differ in the following aspects:statement,data quality,and ***,open-source tools designed for multi-label classification also have intrinsic differences in their approaches for data processing and feature selection,which in turn impacts the performance of a multi-label classification *** the near future,we will enhance experimental precision and reinforce the validity of conclusions by employing more rigorous control over variables through introducing expanded parameter *** implications:The observed Macro F1 and Micro F1 scores on real-world datasets typically fall short of those achieved on benchmark datasets,underscoring the complexity of real-world multi-label classification *** leveraging deep learning techniques offer promising solutions by accommodating the hierarchical relationships and interdependencies among *** ongoing enhancements in deep learning algorithms and large-scale models,it is expected that the efficacy of multi-label classification tasks will be significantly improved,reaching a level of practical utility in the foreseeable ***/value:(1)Seven multi-label classification methods are comprehensively compared on three real-world datasets.(2)The TextCNN and

关键词： Multi-label classification Real-World datasets Hierarchical structure Classification system Label correlation Machine learning

维普期刊数据库