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检索条件"任意字段=International Conference on Intelligent and Smart Computing in Data Analytics, ISCDA 2020"

共 3255 条记录，以下是2041-2050 订阅

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Hyperparameter Analysis of Temporal Graph Convolutional Network Model Applied to Traffic Prediction 12th

Hyperparameter Analysis of Temporal Graph Convolutional Netw...

引用

12th EAI international conference on Simulation Tools and Techniques, SIMUtools 2020

作者： Huang, Jing Chen, Lei An, Yuan Zhang, Kailiang Cui, Ping Jiangsu Province Key Laboratory of Intelligent Industry Control Technology Xuzhou University of Technology Xuzhou221018 China

ISBN: (纸本)9783030727918

GCN based on time and space is an essential part of smart city construction because it can capture the spatiotemporal dynamics and effectively analyze the traffic data to get the best prediction results. In the specific operation of the model, the adjustment and optimal selection of super parameters can make the model provide the best results, thus saving time, cost and computing power. When it comes to the prediction scenarios with low computational power and urgent demand, the existing super parameter search methods and optimization models lack efficiency and accuracy. Therefore, this paper proposes a super parameter search and optimization method based on cross validation, which can efficiently and accurately optimize the parameters, and select the best parameters by using the similarity between the learning and training errors corresponding to each super parameter To improve the prediction ability of the model. Through the verification of the actual data set, the model runs well, and can provide the best prediction results for the traffic flow and other scenarios dominated by spatiotemporal state. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2021.

关键词： Forecasting

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data Analysis of Cricket Score Prediction

Data Analysis of Cricket Score Prediction

引用

international conference on Recent Trends in Machine Learning, IOT, smart Cities and Applications, ICMISC 2020

作者： Srinivas, Suyoga Bhat, Naveen N. Revanasiddappa, M. PES University Bangalore560100 India

ISBN: (纸本)9789811572333

Cricket, a game played on 22-yard strip among 22 players with a bat and ball, is one among the most popular sport in the world. Even though it is played by a lesser number of countries, the sport is followed all across the globe. People are not only interested in following this sport, they also try predicting the flow of the match. Predicting the flow of a cricket match has always been a strenuous task as a particular player may not perform the same way against every opposition nor will his performance be the same in every venue. Also, the way a player performs depends according to the dynamics of the game. While predicting the flow of the match, a majority of the people tend to give more weightage to the previous results. In this paper, we have come up with a model which not only takes previous results into consideration but also the opposition, the venue and the current state of the match such as, number of wickets fallen, number of overs remaining, the way the players have fared till that moment. We have developed various algorithms to find batting and bowling index of the players involved in the match. These indices, along with a special feature, RunFactor form the input parameters to our machine learning model. The generated output from this model is the number of runs that will be scored in the particular over. Compiling these, we estimate the final score scored by that team in a One Day international (ODI). © 2021, Springer Nature Singapore Pte Ltd.

关键词： Forecasting

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Relationship between rice growing environment and diseases-insect pests based on big data analysis

Relationship between rice growing environment and diseases-i...

引用

1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Chen, Yichen Wang, Wanxiong College of Resources and Environmental Science Gansu Agricultural University Lanzhou730070 China

ISBN: (纸本)9789811525674

Rice output directly affects China’s food security. Diseases - insect pests are one of the main agricultural disasters that affect the stable and high yield of crops. With the change of the environment, the variety and scale of diseases and insect pests are increasing. Every year, rice in many areas suffers from diseases and insect pests, which causes serious loss of national food production. Therefore, the research on the relationship between rice growing environment and DIP is increasingly important. At the same time, the emergence of big data analysis enables the growth data of rice and the data of DIP to be analyzed and processed quickly, which provides convenience for this research to a large extent. On the basis of big data analysis, this paper takes rice cultivation as the research object, and through the follow-up investigation of rice DIP in various regions, it can understand the occurrence of rice DIP in different regions in successive years. The relationship between the occurrence of rice diseases and pests and the growth environment factors was discussed, and the climate background and coupling mechanism of the occurrence and prevalence of rice diseases and pests were revealed, so as to predict the occurrence trend of major rice diseases and pests in the region, and to provide basic data for the establishment of disease and pest prediction model. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

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Research on multi- node frame early warning system of power grid based on abnormal data extraction

Research on multi- node frame early warning system of power ...

引用

2020 international conference on Mechatronics Technology and intelligent Manufacturing, ICMTIM 2020

作者： Sui, Bing Chen, Xiaodong Li, Zhengwen Zhao, Jun Tian, Jingfu Liaoning Electric Power Dispatching and Control Center State Grid Corporation of China Shenyang Liaoning110000 China

Nowadays, the collection of electrical energy measurement data is mainly completed by smart meters, electrical energy data monitoring equipment and electrical energy data management equipment. Due to system defects, equipment failures and human factors, it is prone to abnormal data collection. The design concept of online early warning system for extracting abnormal features of electrical energy data based on multi- node real-time computing framework is proposed in the paper to analyze the hardware and software of the online early warning system for extracting abnormal features of electrical energy data. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： data mining

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The architecture of China’s cross-border e-commerce platform based on the data mining technology

The architecture of China’s cross-border e-commerce platfor...

引用

1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Xu, Xianghui Institute of Finance and Economics of Zhengzhou University of Science and Technology ZhengzhouHenan450064 China

ISBN: (纸本)9789811525674

With the development of the economic globalization and the information globalization, the cross-border e-commerce among countries is growing rapidly. However, due to the requirements of its own characteristics, the existing logistics distribution model cannot keep up with the needs of the cross-border business development, which has become a bottleneck restricting its development. Based on the background of the cross-border e-commerce, this paper analyses the existing logistics model. Combining the advantages and disadvantages of the model, the problems of the unbalanced development of the logistics system, the low level of the logistics informationization, the lagging level of the systematic management of the customs and the lack of the financial risk prevention mechanisms in the development of the cross-border e-commerce logistics in China are discussed. Suggestions for the development and construction of the integrated logistics platform are given, and the cohesion between the cross-border e-commerce logistics and the e-commerce platform is also analyzed in details. © Springer Nature Singapore Pte Ltd. 2020.

关键词： data mining

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1st international conference on intelligent computing Techniques for smart Energy Systems, ICTSES 2018

1st International conference on Intelligent Computing Techni...

引用

1st international conference on intelligent computing Techniques for smart Energy Systems, ICTSES 2018

ISBN: (纸本)9789811502132

The proceedings contain 111 papers. The special focus in this conference is on international conference on intelligent computing Techniques for smart Energy Systems. The topics include: intelligent power sharing control for hybrid system;GWO based PID controller optimization for robotic manipulator;a 26 W power supply based on luo converter with improved power factor and total harmonic distortion;optimal strategic bidding using intelligent gravitational search algorithm for profit maximization of power suppliers in an emerging power market;synchrophasor measurements assisted Naïve bayes classification based real-time transient stability prediction of power system;device modeling and characteristics of solution processed perovskite solar cell at ambient conditions;control and remote sensing of an irrigation system using ZigBee wireless network;Analysis and classification of maximum power point tracking (MPPT) techniques: A review;A study and comprehensive overview of inverter topologies for grid-connected photovoltaic systems (PVS);IOT based smart writer;design and implementation of arduino based control system for power management of household utilities;comparative analysis of various classifiers for gesture recognition;Interfacing python with DIgSILENT power factory: Automation of tasks;recent development in perovskite solar cell based on planar structures;artificial intelligence based optimization techniques: A review;optimal location and sizing of microgrid for radial distribution systems;constraint tariff model to reduce the amount of cross subsidy incorporated in electricity tariff using iterative optimization technique;titration machine: A new approach using arduino;hybrid method for cluster analysis of big data;a new radio frequency harvesting system;optical gain tuning in type-I Al0.45Ga0.55As/GaAs0.84P0.16/Al0.45Ga0.55As Nano-heterostructure.

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Identifying People Based on Machine Learning Classification of Foods Consumed in Order to Offer Tailored Healthier Food Options 3rd

Identifying People Based on Machine Learning Classification ...

引用

3rd international conference on intelligent Human Systems Integration (IHSI) - Integrating People and intelligent Systems

作者： Kim, Jenna Lin, Shuhao Ferrara, Giannina Hua, Jenna Seto, Edmund Univ Washington Comp Sci Dept Seattle WA 98195 USA Univ Illinois Dept Kinesiol & Nutr Chicago IL 60612 USA Inst Hlth Metr & Evaluat Seattle WA 98121 USA Stanford Univ Stanford Prevent Res Ctr Stanford CA 94305 USA Univ Washington Sch Publ Hlth Seattle WA 98195 USA

ISBN: (纸本)9783030395124;9783030395117

Using food recall data collected from over 8000 Americans, we used Machine Learning to classify a person's demographic characteristics (age, gender, race, and income) based on the foods they consumed in a 24-h period. The best-performing models predicted gender correctly 61%, race 44%, and age 43% of the time on independent validation data. The model was subsequently used to provide tailored recommendations for healthier food options based on low-calorie and low-fat options for specific food groups that are typically consumed by other Americans that match the person's demographics. This system is part of a larger smart Human-Centered System that assists users in recording the foods they consume, recognizes nutritional content of the food, offers tailored recommendations for consuming healthier foods, and tracking behavior change over time.

关键词： intelligent interfaces for Human-Artificial systems Artificial intelligence Diet and nutrition Health

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Construction of supply chain information sharing mode in big data environment

Construction of supply chain information sharing mode in big...

引用

1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Liu, Jiahui Lu, Guangqiu Wang, Haiqin Qingdao Binhai University QingdaoShandong266555 China

ISBN: (纸本)9789811525674

With the complexity of supply chain network structure and the globalization of supply chain development, information sharing in supply chain becomes more and more important. Supply chain information sharing can not only improve the overall performance of the supply chain, promote cooperation and communication between supply chain nodes, reduce the "bullwhip effect" caused by information non-sharing, but also improve the response speed of supply chain to customer demand, which is conducive to the formation of core competitiveness of enterprises. With the arrival of the era of big data, information sharing has new opportunities and corresponding challenges in supply chain: on the one hand, the development of new technologies such as cloud computing and big data analysis technology has provided new sharing modes and channels for information sharing in supply chain;on the other hand, most of them have to face challenges. According to the storage and processing of massive information caused by massive data in the environment, new challenges are posed to enterprises. Based on the change of information sharing in supply chain under big data environment, it is very important to build a new information sharing mode. Based on the analysis of the advantages and disadvantages of three traditional information sharing modes, this paper constructs an identity-based and role-based information sharing mode using advanced storage platform and data prediction and mining methods in large data environment, which solves the problem of limited data storage and operation speed. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

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Personal Information Security Risks and Legal Prevention from the Perspective of Network Security

Personal Information Security Risks and Legal Prevention fro...

引用

international conference on Cyber Security Intelligence and analytics, CSIA 2020

作者： Wang, Zhe Fuzhou University of International Studies and Trade Fuzhou350202 China

ISBN: (纸本)9783030433055

In the era of big data, with the advancement of information technology and the popularization of mobile Internet, digital life has brought great convenience to people, and also brought a series of social problems. In recent years, large-scale leakages of citizens’ personal information have occurred from time to time, and the citizens’ rights and interests have been damaged and it is difficult to get timely relief. The leakage of personal information and data has also become an issue of increasing concern. This paper first introduces the basic overview of personal information security risks from the perspective of network security, then states the legal problems of personal information network security risks, and finally proposes corresponding countermeasures. © Springer Nature Switzerland AG 2020.

关键词： Cybersecurity

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A Role of Law in Network Security Supervision Based on Public Internet Perspective

A Role of Law in Network Security Supervision Based on Publi...

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international conference on Cyber Security Intelligence and analytics, CSIA 2020

作者： Chen, Caihong Fuzhou University of International Studies and Trade Fuzhou350202 China

ISBN: (纸本)9783030433055

In recent years, with the accelerated implementation of national big data development strategies, the innovation and application of big data technology have become increasingly active, generating and aggregating massive types of network data with increasing types and increasing application values, which have become key production factors for the development of the digital economy. Common network security problems include leaking user information without permission, abusing and disseminating data through the Internet, and conducting illegal transactions, etc., and there is an upward trend. Therefore, it is particularly urgent to manage network data security in the Internet industry. Network security issues are emerging one after another. This requires us to study how to prevent and respond to endless network security issues in the context of big data, and how to give full play to the legal role in network security supervision in order to face the new era of new technologies. Threats and challenges. © Springer Nature Switzerland AG 2020.

关键词： Network security

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