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World conference on Earthquake Engineering proceedings 2024年 2024卷

作者： Hariri-Ardebili, M.A. Salamon, J.W. University of Maryland College Park United States US Bureau of Reclamation Denver United States

Despite the significant advances in nonlinear dynamic analysis of engineering structures, concerns still exist regarding the level of confidence in modeling and the accuracy of analysis outcomes. While verification and validation of computational processes are primary tools used to quantify the accuracy of solutions and to build confidence in the analysis results, they cannot fully eliminate sources of uncertainties during performance evaluation. In particular, uncertainties in the dynamic analysis of dam-water-rock coupled systems can be attributed to both epistemic and aleatory sources of uncertainties. This paper focuses on the importance of addressing epistemic uncertainties in the seismic analysis of a gravity dam through careful data collection from the 15th ICOLD’s Benchmark Workshop organized in Milan, Italy in 2019. In the case study formulation, the geometry of the model, mechanical properties of materials, and loads were precisely defined, and participants were asked to analyze the defined cases selecting the best practice in modeling and simulation of concrete dams. Significant variability was observed in contributions, particularly in the application of the far-field boundary conditions and the non-linear material models selected for concrete damage modeling. This paper elaborates further on the sources of various variabilities and attempts to quantify the amount of uncertainty in modeling and simulation for such well-defined benchmark problems. The results of this study emphasize the need for establishing a systematic approach to modeling and analyzing seismic hazards in dam engineering to improve the accuracy and consistency of predictions. A better understanding of the sources and magnitudes of modeling uncertainties can help improve the reliability of dam analyses, contribute to the development of more effective risk assessment and mitigation strategies, and build confidence in the analysis results. © 2024, international Association for Earthquake E

关键词： Concrete dams

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modeling and analysis of the Influence of College Students’ Cultural Confidence Based on KPCA Algorithm 3rd

Modeling and Analysis of the Influence of College Students’...

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3rd EAI international conference on Application of big data, Blockchain, and Internet of Things for Education Informatization, bigIoT-EDU 2023

作者： Zong, Yanyan Ai, Xizhen Qing, Keri Hefei University Anhui Hefei230601 China Luoyang Institute of Science and Technology Henan471000 China

ISBN: (纸本)9783031631320

Cultural self-confidence is a kind of self-esteem based on cultural values and beliefs. College students’ cultural self-confidence is a person's perception of college students’ cultural identity. College students’ cultural self-confidence is defined as "a person's self-awareness of their college students’ culture and the degree to which they feel comfortable in the cross-cultural environment of college students". College students’ cultural self-confidence has been proved to be related to many different results, such as educational achievements, socialization and healthy behavior of integrating foreign college students’ culture. In this paper, this study aims to develop a more objective and accurate new method to measure cultural self-confidence. Using KPCA algorithm, I will discuss how college students’ cultural self-confidence exists. Cultural self-confidence is considered to be an important part of cultural self-esteem and plays an important role in students’ academic performance. As an ideal personality under Chinese culture, gentleman personality has been proved to have a significant impact on prosocial behavior, but the relationship between it and online prosocial behavior is still unclear. As an important psychological function, self-control has been shown by a large number of studies to have a significant impact on individual behavior, and has been confirmed by studies that self-control is an important part of the "self-denial" advocated by Confucianism in the personality of a gentleman. The purpose of this study is to use Kpca algorithm to investigate the relationship between cultural self-confidence and academic achievement of Iranian college students. This study adopts the relevant design, pre-test and post-test experimental design. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Students

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analysis of Spatial-temporal Variation Characteristics of Vegetation in the Yellow River Source Region from 1982 to 2019 2

Analysis of Spatial-temporal Variation Characteristics of Ve...

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2nd international conference on big data and Artificial Intelligence and Software Engineering (ICBASE)

作者： Gao, Siqi Liu, Jun Dong, Guotao Jiang, Xiaohui Yin, Huijuan Lei, Yuxin Nie, Tong Northwest Univ Coll Urban & Environm Sci Xian 710127 Peoples R China YRCC Ningxia Inner Mongolia Hydrol & Water Resources B Baotou 014030 Peoples R China Yellow River Conservancy Commiss Yellow River Inst Hydraul Res Zhengzhou 450003 Peoples R China Heihe Water Resources & Ecol Protect Res Ctr Lanzhou 730030 Peoples R China

ISBN: (纸本)9781665427098

As an important component of surface cover, the changes of vegetation can reflect the changes of regional environment at different spatial and temporal scales, and the normalized difference vegetation index (NDVI) based on remote sensing can effectively reflect the growth status of surface vegetation, and the study of the spatial and temporal characteristics of NDVI changes of vegetation in long time series can help the protection and sustainable development of regional ecological environment. In this study, based on the overlapping period data of Global Inventory modeling and Mapping Studies (GIMMS) NDVI from 1982 to 2015 and Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI from 2000 to 2019 in the Yellow River source region (YRSR), we established the GIMMS NDVI dataset from 1982 to 2019 in the YRSR, and analyzed the spatial and temporal characteristics of vegetation NDVI changes in the YRSR for 38 years by using linear regression analysis, accumulative anomaly method and moving ttest method. The results showed that the spatial distribution of NDVI in the YRSR was high in the southeast and low in the northwest, and the spatial trend was increasing in the north and decreasing in the center. The mean NDVI from 1982 to 2019 showed an overall weak increasing trend, with abrupt changes in NDVI in 2000 and 2008. This study will contribute to a better understanding of the vegetation cover changes in the YRSR, which is of great significance for the ecological protection of the YRSR.

关键词： NDVI GIMMS MODIS Spatial-temporal Variation Yellow River Source Region

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The Research of Quantitative Evaluation Algorithm of Process Auto Alarm analysis Based on Chem-HRA

The Research of Quantitative Evaluation Algorithm of Process...

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2020 international conference on modeling, big data Analytics and simulation, MBDAS 2020

作者： Jiang, Xue Dang, Wenyi Research Institute of Safety Engineering SINOPEC Qingdao China

For the process alarm management of chemical process safety analysis, its reliability mainly depends on the design of the safety limit and the optimization of the technical process, but there are few studies on the overall reliability level of process alarm based on the alarm disposal rate under the influence of human factor reliability. By focusing on independent layer analysis technique in the alarm and response, we combined the human reliability analysis (HRA) technology and Bayes theory, to form Human Reliability analysis in chemical process safety(Chem-HRA), an optimized quantitative evaluation algorithm for chemical alarm failure frequency. The algorithm was applied to a risk event on tank farm's cut over, ensuring the reliability and accuracy of petrochemical process analysis and disposal of the process alarm. © Published under licence by IOP Publishing Ltd.

关键词： Reliability analysis

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Analyzing the Financial Impact of ESG News Sentiment on ESG Finance Trends

Analyzing the Financial Impact of ESG News Sentiment on ESG ...

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international conference on Platform Technology and Service (PlatCon)

作者： Minjoong Kim Sujin Kim Yongsung Kim Jihoon Moon Dept. of ICT Convergence Soonchunhyang University Asan South Korea Graduate School of Education Chungnam National University Daejeon South Korea Dept. of Technology Education Chungnam National University Daejeon South Korea Dept. of AI and Big Data Soonchunhyang University Asan South Korea

ISBN: (数字)9798350367874

ISBN: (纸本)9798350367881

This paper examines the interconnections between environmental, social, and governance (ESG) financial trends and the sentiment analysis of ESG-related news from 2019 to 2022. A substantial corpus of news articles and ESG management data is subjected to analysis employing a range of techniques, including term frequency-inverse document frequency (TF-IDF), latent Dirichlet allocation (LDA) topic modeling, and sentiment analysis tools such as valence-aware dictionary and sentiment reasoner (VADER) and bidirectional encoder representations from transformers (BERT). This analysis identifies significant trends and relationships between sentiment direction, ESG ratings, and financial performance. The results demonstrate that while ESG ratings do not have a robust direct correlation with financial metrics, sentiment analysis of ESG news offers insights into the potential impact of ESG management. This study underscores the necessity for standardized ESG metrics to enhance the clarity and efficacy of measuring the financial impact of ESG management. These insights are intended to inform the formulation of policies and strategies for future ESG management.

关键词： Measurement Sentiment analysis Analytical models Correlation Finance Network analyzers Market research Transformers Resource management Radio spectrum management

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analysis of Chaotic Behavior in Single Mode NH3 Molecular Laser 2nd

Analysis of Chaotic Behavior in Single Mode NH3 Molecular La...

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2nd international conference on IoT and big data Technologies for HealthCare, IoTCare 2021

作者： Zang, Hongyan Zhang, Shourong Lei, Tengfei Qilu Institute of Technology Jinan250200 China Shandong Vanform High Energy Physics Technology Jinan250200 China

ISBN: (纸本)9783030941819

In this paper, a single-mode NH3 molecular laser system is introduced. Firstly, the basic dynamic behaviors of the laser system such as bifurcation diagram, Lyapunov exponent and complexity C0 are analyzed by numerical simulation using MATLAB, and the chaotic characteristics of the laser system and its sensitivity to parameters are described. At the same time, in order to further study the influence of its parameters, the relationship between the system period and the existence of chaos is studied by using the complexity C0 under the change of two parameters. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： MATLAB

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Window-Based Dynamic Streaming Tensor analysis Based on CP Decomposition 4

Window-Based Dynamic Streaming Tensor Analysis Based on CP D...

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4th international conference on Artificial Intelligence and big data, ICAIBD 2021

作者： Zhong, Xuemei Chen, Junhua Zhang, Lei Zhang, Yan Key Laboratory of Industrial Internet of Things Networked Control Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9780738131702

With the growing demand of big data mining, tensor as a tool representing multidimensional data is wild used in many systems. Then, streaming tensor analysis approaches have come forth for streaming data mining. With the generation of more and more high-velocity streaming data, data analysis beyond traditional offline needs to be transformed into efficient online processing to keep from cost of re-modeling and re-decomposition. In addition, existing work on streaming tensor analysis is usually based on Tucker decomposition, and assumes that tensors are not scalable in streaming media settings(i.e., each time stamp comes a tensor with the same order and dimension), such as incremental tensor analysis(ITA), which restricts the use of Tucker decomposition for dynamic streaming tensor analysis. CANDECAMP/PARAFAC Decomposition(CP) decomposition as a special case of Tucker decomposition, can also be used to analyze streaming data. However, there are very limited studies on dynamic streaming tensor tracking based on CP decomposition. To fill these gap, this paper establishes a tensor stream model for dynamic streaming data and proposes an efficient online algorithm named window-based dynamic streaming tensor analysis based on CP decomposition (CP_WTA) that can analyze dynamic streaming tensor(i.e., each time stamp comes a tensor with the different dimensions in a certain mode). This paper also proposes its two variants, namely independent-window-based streaming tensor analysis (IW) and sliding-window-based streaming tensor analysis (SW). The effectiveness of the proposed methods are proved by extensive evaluation on actual data sets. © 2021 IEEE.

关键词： Tensors

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Time Series Prediction of day-ahead Photovoltaic Power Based on data-Driven 4

Time Series Prediction of day-ahead Photovoltaic Power Based...

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4th IEEE China international Youth conference on Electrical Engineering, CIYCEE 2023

作者： Zhang, Mingyue Han, Yang Yan, Chaofeng Yang, Ping Wang, Congling University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu611731 China

ISBN: (纸本)9798350305562

This paper introduces a comprehensive forecasting model that integrates kernel principal component analysis (KPCA), grey wolf optimizer (GWO) and light gradient boosting machine (LightGBM), which aims to address the challenges posed to grid scheduling by large-scale photovoltaic (PV) grid connection. Firstly, KPCA is used to identify key factors influencing PV power, selecting correlated meteorological data as relevant features. These features and historical power data are used to train the LightGBM model. GWO optimization is applied to prevent the model from getting stuck in local optima, resulting in highly accurate ultra-short-term PV power predictions. The simulation results demonstrate that the GWO-optimized LightGBM significantly enhances prediction accuracy, reducing the mean absolute percentage error (MAPE) by 4.482% and the root mean square error (RMSE) by 0.289 kW. Furthermore, this proposed model surpasses XGBoost, achieving a reduction in MAPE and RMSE by 7.324% and 0.394 kW, respectively. These findings suggest that the proposed model effectively captures the variability in photovoltaic power and delivers more consistent prediction results. This research represents a promising avenue for further exploration in the field of ultra-short-term PV power prediction. © 2023 IEEE.

关键词： Forecasting

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Performance analysis of big data transmission in wearable system based on special textile clothing 10

Performance analysis of big data transmission in wearable sy...

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10th Annual international conference of Information and Communication Technology (ICICT)

作者： Zhang, Yi Li, Jian Wuhan Text Univ E&E Wuhan Peoples R China Wuhan Text Univ Hubei Key Lab Digital Text Equipment Wuhan Peoples R China

Special textile clothing covers a wide range. It includes helmet, vest, coat, trousers and boots. In the home environment, wearable devices can monitor the physiological parameters of the elderly or children according to the requirements. These physiological parameters include EEG, heart rate, blood pressure, blood glucose, height, weight, walking speed and standing posture. The acquisition and remote transmission of these parameters are very important for the monitored and information center. Therefore, it is necessary to analyze and simulate the transmission performance of data. This work mainly introduces the principle of performance analysis, simulation model and numerical calculation. simulation results show that the proposed scheme can still improve the quality of service under the same network conditions. (C) 2021 The Authors. Published by Elsevier B.V.

关键词： Blood pressure standing posture remote transmission acquisition

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An Empirical Study on the Impact of Innovation and Entrepreneurship Policies on Regional Innovation Capabilities Based on the Double-Difference Model 22

An Empirical Study on the Impact of Innovation and Entrepren...

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Proceedings of the 2022 5th international conference on E-Business, Information Management and Computer Science

作者： Lin Wang Min Peng Wuhan Business University China

ISBN: (纸本)9781450397827

The rapid development of cloud computing and big data technology provides technical support and method guarantee for regional innovation and development. Innovation and entrepreneurship are the core strategies for enhancing national competitiveness, and the establishment of regional demonstration bases for innovation and entrepreneurship is an important path for implementing the national innovation strategy. Methods: Based on cloud computing and big data modeling technology, the panel data of 70 prefecture-level cities in the Yangtze River Economic Belt urban agglomeration from 2014 to 2019 were collected, and through the double difference model, two batches of regional demonstration bases for innovation and entrepreneurship established by the state in 2016 and 2017 were used. data modeling for research subjects. Objective: To study the influence and driving factors of the establishment of innovation and entrepreneurship regional demonstration bases on regional innovation capability. Conclusion: The establishment of the regional demonstration bases for innovation and entrepreneurship has an obvious role in promoting regional innovation capabilities; the establishment of regional demonstration bases for innovation and entrepreneurship significantly promotes the development of regional innovation capabilities in the upper, middle and lower reaches of the Yangtze River Economic Belt; The effect of ability is not significant.

关键词： Regional innovation capability The Yangtze Economic Belt big data analysis Double-difference model

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