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Flood Prediction Using Rainfall-Flow Pattern in Data-Sparse Watersheds

IEEE ACCESS 2020年 8卷 39713-39724页

作者： Zhu, Yuelong Feng, Jun Yan, Le Guo, Tao Li, Xiaodong Hohai Univ Comp & Informat Coll Nanjing 211100 Peoples R China

Real-time flood forecasting of small- and medium-sized rivers in areas with scarce hydrological data is an urgent problem that needs to be solved. Traditional hydrological model parameters cannot be fully trained owing to a lack of data;thus, results obtained by such models are not satisfactory. We need a new way to solve the forecasting problem for small- and medium-sized rivers. We found that the time series of some feature variables have evident change trajectories in spatial dimension, and the change of some feature variables in the spatial dimension has a decisive influence on flooding processes, such as the spatial distribution of rainfall. To reflect the change of feature variables in spatial dimension with to solve the problem of the lack of hydrological data, we constructed a rainfall-flow pattern composed of a spatial-temporal dynamic time warping algorithm and multi-feature algorithm to measure the similarity of hydrological time series. In the experimental watersheds, we used rainfall-flow patterns to forecast the short-term flood streamflow, and satisfactory results were obtained. This suggests that the algorithm is suitable for hydrological studies and improves the accuracy of real-time flood forecasting for longer forecast periods.

关键词： Spatiotemporal sequence data rainfall-flow pattern matching similarity measurement algorithm multi-feature algorithm ST-DTW algorithm

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Research on Student Course Selection on Learning Behavior Analysis algorithm Based on data Mining 2

Research on Student Course Selection on Learning Behavior An...

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Yu, Xiaoting Modern College of Northwest University Xi'an City China

ISBN: (纸本)9798350317558

With the popularization of higher education, the problem of students' course selection behavior has gradually become prominent. Based on the in-depth investigation of students' course selection behavior, this study identifies the main existing problems and puts forward corresponding countermeasures. It is found that students have blindness and utilitarianism in choosing courses, which leads to unreasonable knowledge structure and affects their studies. In view of these problems, this paper puts forward corresponding solutions to help students choose courses more scientifically. © 2024 IEEE.

关键词： data mining algorithms Pearson correlation coefficient theory similarity measurement algorithm Student behavior analysis student course selection algorithm

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Application of Collaborative Filtering algorithm of Resource Management Software in Community Service 3

Application of Collaborative Filtering Algorithm of Resource...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Li, Qin Mianyang Teachers' College Sichuan Province Mianyang City621000 China

ISBN: (纸本)9798350319125

The role of resource management software in community service is very important, but there is a problem of inaccurate outcome evaluation. The similarity measurement algorithm cannot solve the resource management software problem in community service, and the evaluation is unreasonable. Therefore, this paper proposes a collaborative filtering algorithm for resource management software analysis. Firstly, the Pearson correlation coefficient theory is used to evaluate the resource management software, and the indicators are divided according to the requirements of the resource management software and reduced Distractions in resource management software. Then, Pearson's correlation coefficient theory forms a resource management software scheme for resource management software and synthesizes the results of resource management software Analyze. THERLOY shows that in the case of certain evaluation criteria, collaborative filtering algorithms serve the community The accuracy of resource management software and the time of resource management software are better than the similarity measurement algorithm. © 2023 IEEE.

关键词： collaborative filtering algorithm community service Pearson correlation coefficient theory similarity measurement algorithm

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Design of Cold Chain Logistics Monitoring System based on ZigBee and GPS Positioning Technology 3

Design of Cold Chain Logistics Monitoring System based on Zi...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Hongmin, Pan Shandong Institute of Commerce and Technology Shandong Jinan China

ISBN: (纸本)9798350319125

The role of monitoring system design in cold chain logistics transportation is very important, but there is a problem of inaccurate evaluation of results. The similarity measurement algorithm cannot solve the problem of monitoring system design in cold chain logistics transportation, and the evaluation is unreasonable. Therefore, this paper proposes a ZigBee and GPS positioning technology for monitoring system design analysis. Firstly, the relevant theory of Darwinian evolution is used to evaluate the design of the monitoring system, and the indicators are divided according to the design requirements of the monitoring system and reduced Monitor interference factors in system design. Then, Darwin's evolution-related theory designs the monitoring system, forms the monitoring system design scheme, and synthesizes the monitoring system design results Annalise. THERLOY shows that in the case of certain evaluation criteria, ZigBee and GPS positioning technology The design accuracy and design time of the monitoring system for cold chain logistics transportation were better than the similarity measurement algorithm. © 2023 IEEE.

关键词： cold chain logistics transportation Darwinian evolution-related theory Monitoring system design similarity measurement algorithm ZigBee and GPS positioning technology

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