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GA-SVR Traffic Flow Prediction Based on Phase Space Reconstruction with Improved KNN Method 25

GA-SVR Traffic Flow Prediction Based on Phase Space Reconstr...

引用

25th IEEE International Conference on computer Supported Cooperative Work in Design, CSCWD 2022

作者： Li, Jia Xu, Gang Huang, Baoqi Bai, Xiangyu Inner Mongolia A.R. Key Laboratory of Wireless Networking and Mobile Computing Hohhot010021 China College of Computer Science Inner Mongolia University Hohhot010021 China

ISBN: (纸本)9781665405270

Traffic flow prediction plays an important role in intelligent traffic management. In order to solve the problem that the prediction model has low accuracy in traffic flow prediction when the amount of data is small. Considering the chaotic nature of the traffic flow time series data, the phase space reconstruction method is adopted to process the data, and then the SVR model is used to predict the processed data. The two parameters of phase space reconstruction, including embedding dimension and delay time, have a great impact on the final prediction accuracy. In this paper, the improved KNN method is used to select the parameters of phase space reconstruction and construct the KNN-GA-SVR model. Compared with the CC-GA-SVR model of phase space parameter selection based on C-C method, this model improves the prediction accuracy, is effective and feasible for the prediction of short-term traffic flow, and has strong applicability. © 2022 IEEE.

关键词： Support vector machines

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Short-Time Traffic Flow Prediction Based on K-means++ and LSTM 20

Short-Time Traffic Flow Prediction Based on K-means++ and LS...

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20th IEEE International Symposium on Parallel and Distributed Processing with Applications, 12th IEEE International Conference on Big Data and Cloud computing, 12th IEEE International Conference on Sustainable computing and Communications and 15th IEEE International Conference on Social computing and networking, ISPA/BDCloud/SocialCom/SustainCom 2022

作者： Li, Jia Xu, Gang Cheng, Yuan Huang, Baoqi Inner Mongolia A.R. Key Laboratory of Wireless Networking and Mobile Computing Hohhot010021 China College of Computer Science Inner Mongolia University Hohhot010021 China

ISBN: (纸本)9781665464970

With the gradual increase in the number of vehicles owned by people, the problem of urban traffic congestion is becoming more and more serious. Timely and accurate traffic flow prediction helps travel vehicles to plan their routes reasonably, avoid congested roads and reduce environmental pollution. In order to take full advantage of the daily periodicity of the traffic flow of a road section, K-means++ with improved initial clustering centroids is applied to analyze the similarity of the daily traffic flow patterns and classify the traffic flow patterns with day as the time interval. One can separate the traffic patterns affected by different factors, and the other can exclude individual days containing abnormal data trends formed by unexpected road conditions, which can save the deep learning model from the interference of other irrelevant data features. Finally, a Long Short-Term Memory (LSTM) model is combined to predict the traffic flow value at the next time point based on the data of the previous hour. In the experiment, the K-means-LSTM model can significantly reduce the prediction error of short-time traffic flow and has better prediction performance by comparing with the prediction results of the support vector machine (SVR) model optimized by genetic algorithm (GA) and the LSTM model. © 2022 IEEE.

关键词： Long short-term memory

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Progress and Challenges of Polymorphic Smart Networks

Progress and Challenges of Polymorphic Smart Networks

引用

Asia-Pacific Network Operations and Management Symposium (APNOMS)

作者： Peixin Liu Xiangyu Bai Zhaoran Wang Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing College of Computer Inner Mongolia University Hohhot China

The current Internet infrastructure and technology system faces major challenges in intelligent, diversified, personalized, highly robust, efficient and other aspects, and it is urgent to reform the network infrastructure. Polymorphic smart network (PINet), as an open network architecture based on full-dimensional definable technology, has been studied by more and more scholars. This paper first introduces the architecture of polymorphic smart network, then introduces the key technologies and related research of polymorphic smart network, then describes its simulation environment, and finally expounds the existing problems and possible breakthrough technologies and key points of PInet.

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An Overview of Intelligent Algorithm-Based Routing in Delay Tolerant Networks

An Overview of Intelligent Algorithm-Based Routing in Delay ...

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International Conference on computers, Communications, and Systems (ICCCS)

作者： Lei Yao Xiangyu Bai Zhaoran Wang Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing College of Computer Inner Mongolia University Hohhot China

Delay tolerant network (DTN) is a new paradigm with the development of wireless technology and mobile Ad-hoc network (MANET). Unlike the stable end-to-end connection in the traditional network, the storage - carry - forward mode is adopted in DTN. Routing optimization is the most basic problem in delay tolerant network. It assumes the heavy responsibility of data transmission, and even determines the performance of the whole network. In recent years, with the development of artificial intelligence, there have been many researches on the use of AI to optimize the routing in DTN. However, the relevant literature is insufficient at present. In this paper, we first introduce the methods related to artificial intelligence, and then summarize and discuss the existing literature from five parts: machine learning classifier, prediction task using machine learning, biological heuristic method, reinforcement learning and artificial intelligence assistance.

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Analysis and Comparison of Delay Tolerant Network Security Issues and Solutions

Analysis and Comparison of Delay Tolerant Network Security I...

引用

IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Jingwen Su Xiangyu Bai Kexin Zhou Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing College of Computer Inner Mongolia University Hohhot China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Delay Tolerant Network (DTN) is a network model designed for special environments. It is designed to be used in challenging network environments with high latency levels, bandwidth constraints, and unstable data transmission. It plays an important role in extremely special environments such as disaster rescue, maritime communication, and remote areas. Currently, research on DTN mainly focuses on innovative routing protocols, with limited research of the security issues and solutions. In response to the above problems, this paper analyzes and compares the security problems faced by delay tolerance networks and their solutions and security schemes.

关键词： Privacy Disasters Bandwidth Network security Routing protocols Delays Data communication

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Review of Ecological Environment Monitoring Methods of Northern Wetland in inner mongolia Based on WSN

Review of Ecological Environment Monitoring Methods of North...

引用

IEEE International Conference on Communication and Information Systems (ICCIS)

作者： Wenyu Li Xiangyu Bai Kexin Zhou Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing College of Computer Inner Mongolia University Hohhot China

Wetland ecosystem is a special ecosystem, which refers to the area where water and land intersect, including swamps, rivers, lakes, estuaries, bays, etc. These areas usually have special biodiversity and ecological functions, which are of great significance to both human beings and the natural environment. In recent years, the northern wetland ecosystem of inner mongolia with Hulun Lake, Wuliangsuhai Lake and Daihai Lake as the core, is facing the problems of reduced water area, poor water quality and serious pollution due to natural and human factors, which has begun to affect other environmental changes and hindered social and economic development. It is urgent to monitor the ecological environment and control pollution in relevant areas. The core of environmental monitoring is data collection. The traditional data acquisition methods have some defects, such as high cost and low efficiency. This paper proposes to use wireless sensor network to carry out long-term automatic monitoring of ecological environment in this area, and summarizes the relevant experience and technology.

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A Review of Network Resource Scheduling in Distance Education Scenarios

A Review of Network Resource Scheduling in Distance Educatio...

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International Conference on computer and Communications (ICCC)

作者： Qingqing Zhao Xiangyu Bai Kexin Zhou Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing College of Computer Inner Mongolia University Hohhot China

With the rapid development of the Internet, resource scheduling in distance education scenarios faces new opportunities and challenges. In the context of large-scale distance education, how to realize rational scheduling of network resources is an issue worthy of systematic research. From the perspective of distance education, this paper provides an overview of the multiple factors that need to be considered in the current scheduling of distance education network resources, as well as the development of related optimization algorithms and network technologies. At the same time, the future development direction and trend are proposed for the problems and challenges faced by distance education network resource scheduling. In order to improve the utilization of network resources and the learning effect of students, the rational scheduling of network resources in distance education scenarios still needs continuous exploration and research.

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Research on Malicious Account Detection Mechanism of Ethereum Based on Community Discovery

Research on Malicious Account Detection Mechanism of Ethereu...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Min Li Bo Cui Wenhan Hou Ru Li Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing College of Computer Science Inner Mongolia University Hohhot China

Blockchain has facilitated the growth of cryptocurrencies but has also provided new ideas for illegals to commit fraud. Research on malicious accounts detection shows that the number of malicious accounts is much smaller than that of benign accounts, leading to imbalanced dataset samples. Most researchers adopt the under-sampling method to help deal with this issue, but this method does not correspond to the actual scale. So, we propose an anomaly detection method based on community discovery. Firstly, we use the transaction information in the Ethereum public chain to build a transaction network and use the Louvain algorithm to divide the transaction network into communities. Secondly, we use the LightGBM algorithm to classify the community. Finally, based on the classification results, we use HBOS, LOF, K-Means, KNN and iForest algorithms as benchmark algorithms for anomaly detection and compare the experimental results using the methods in this paper with the results of anomaly detection using the original transaction network. Experimental show that our method can reduce the amount of data by 35.53% and increase the AUC values of the five algorithms by 7.52%, 8.41%, 14.88%, 0.83% and 27.95%.

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Research on Fine-grained Security Sharing Model of Medical Information Based on Blockchain

Research on Fine-grained Security Sharing Model of Medical I...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Bo Cui Zeyu Chen Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing College of Computer Science Inner Mongolia University Hohhot China

In light of the vulnerabilities in traditional medical information systems, including the susceptibility to malicious tampering of patients’ medical records, opaque access decisions, and challenges in data sharing, this paper introduces a fine-grained security sharing model for medical information based on blockchain. Firstly, it leverages blockchain technology in conjunction with attribute-based access control to automate multi-authority fine-grained access control through smart contracts. Secondly, it categorizes sensitive attributes of different users and electronic medical records into distinct levels, implementing personalized privacy protection within the transaction workflow using local differential privacy policies and varying privacy budgets. Finally, a prototype system, built upon a consortium blockchain, was developed and tested using a dataset of 100,000 real-world electronic medical records. Experimental results demonstrate the model’s capability to facilitate stable and reliable transactions between electronic medical record publishers and requestors while ensuring privacy protection.

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Research on the Application of Drone Remote Sensing and Target Detection in Civilian Fields

Research on the Application of Drone Remote Sensing and Targ...

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High Performance Big Data and Intelligent Systems (HPBD&IS)

作者： Xiaochen Gao Xiangyu Bai Kexin Zhou Inner Mongolia Key of Wireless Networking and Mobile Computing College of Computer Inner Mongolia University Hohhot China

Unmanned aerial vehicle (UAV) remote sensing has evolved as an efficient means of geospatial data acquisition. This paper provides a comprehensive review of the key technologies enabling intelligent analysis of UAV remote sensing images, specifically payload technology and object detection algorithms. Main payload systems including optical, multispectral, hyper-spectral, SAR, and LiDAR are introduced, with analyses of their working principles, performance benchmarks, and suitable application scenarios. In terms of object detection, traditional methods and emerging deep learning-based techniques are discussed and compared. The superior capabilities of anchor-free and Transformer-based detectors are analyzed through representative algorithms like CenterNet, FCOS, and DETR. Additionally, case studies demonstrate the broad applications and profound value of UAV remote sensing with intelligent target detection in areas such as precision agriculture, environmental conservation, infrastructure monitoring, and emergency response. Overall, this paper offers an in-depth examination of the landscape and trends of core technologies augmenting UAV remote sensing, providing guidance for future research and applications.

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