检索结果-内蒙古大学图书馆

2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Nandhakumar, R.G. Devi, K. Nirmala Krishnamoorthy, N. Shanthi, S. Pranesh, V.R. Nikhalyaa, S. Kongu Enginering College Perundurai Department of Computer Science and Engineering Tamilnadu Erode India Vellore Institutte of Technology School of Information and Engineering Department of Software Systems and Engineering Vellore India

ISBN: (纸本)9798350348217

Road safety is of prime importance as road accidents are among the biggest causes of deaths in the country. Road Accidents are majorly due to violators and lawbreakers of road safety rules like not wearing helmets, triple riding etc. Even though there are many smart systems to monitor these violations, it is complicated to keep a track of the data and view it efficiently anywhere. Also monitoring the permit details of other state vehicles is hard. A method was proposed to address this issue. based on Deep learning and Optical Character Recognition (OCR). Here we detect the riders not wearing helmet and triple riders using object detection by comparing YOLOv2 and YOLOv3. This simplifies the task of traffic police who can't continuously and efficiently monitor all the violators. We gathered our data from three different sources. Kaggle was used to collect the data set. A number of items can be recognized by the real-time object recognition system YOLO in a single frame. It recognizes object more precisely and faster than other recognition systems. It can predict up to 9000 classes and even unseen classes. It divides the image into m∗m matrix and each grid detects objects within itself. The trained model is tested using a test dataset set after training in order to measure the performance. For Number plate detection we use OCR based character recognition. The recognized license plate images of violators are captured and stored in a database which is then sent to the concerned department. The stored data can be easily accessed using the developed mobile app. Metrics considered for evaluation is Accuracy. The average is utilized to assess object detection models like R-CNN and YOLO. The average calculates a score by comparing the detected box to the ground-truth bounding box. The better the score, the more precise the model's detections are. When compared to YOLOv2, YOLOv3 exhibits strong performance in terms of accuracy with 95.5%. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

A New Hybrid Cuckoo Search for the Resources-Constrained Project Scheduling Problem

IAENG International Journal of Computer Science

引用

IAENG International Journal of computer science 2021年第2期48卷 1-12页

作者： Shen, Xin Zhang, Xiaoxia Yu, Ziqiao X. Shen is a Master Student of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China X. X. Zhang is a Professor of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan11041 China A Master Student of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China

Resource-constrained project scheduling problem (RCPSP) is a kind of representative practical engineering problem, the purpose is to schedule activities in the project through rational use of limited resources in the minimum time. This paper proposes an improved hybrid cuckoo algorithm (CS&SA) to solve the RCPSP problem. Firstly, the individual elements are randomly coded into priority vectors, and the population is decoded using serial scheduling to convert the individual into a set of task scheduling sequences. Secondly, the Levy flight is redesigned to change the algorithm from random walk to adaptive as the population fitness changes. Then, this article adds three neighborhood update techniques to meet the update requirements of the algorithm at different stages. Finally, in order to prevent the algorithm from falling into a local optimum, this paper introduces a simulated annealing strategy to allow the algorithm to accept some individuals with poor quality with a certain probability in each iteration. In the testing part, this paper firstly tests the effectiveness and optimization of three different-scale examples in the classic example library PSPLIB for RCPSP problems. Among them, the average error of the CS&SA algorithm in the small-scale J30 is 0.25%, and the average error in the medium-scale J60 is 11.21%, and the average error of the large-scale J120 is 19.83%. Then, by comparing other intelligent optimization algorithms, it is proved that NCS&SA is superior to other algorithms in optimization and accuracy. © 2021. All Rights Reserved.

关键词： Combinatorial optimization

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Model Based on NeuralProphet and Long Short-Term Memory for Time Series Forecasting

A Hybrid Model Based on NeuralProphet and Long Short-Term Me...

引用

2022 IEEE International Conference on Big Data, Big Data 2022

作者： Yu, Zhaofeng Niu, Kun Chen, Xiao Guo, Zhijun Li, Dongsheng Beijing University of Posts and Telecommunications School of Computer Science National Pilot Software Engineering School Beijing China

ISBN: (纸本)9781665480451

Time series forecasting has historically been a popular research area, attracting widespread interest in academia and industry. Recently, Deep Learning based models like RNN, LSTM, and NeuralProphet have been successfully applied for time series forecasting. However, single forecasting models are unable to capture full information and learn complex patterns in data. The combination of models has proved to be an effective strategy to address this issue. Traditional hybrid structures still limit the forecasting ability of hybrid methods. In this paper, we propose a novel hybrid forecasting model based on LSTM and NeuralProphet (NP-LSTM), which is constructed by a parallel-series hybrid structure. The proposed model uses LSTM to model diverse nonlinear relationships and NeuralProphet is designed to extract primary trends and seasonal effects and provide interpretability. In the experiments of this paper, we compare our model with other single models and hybrid models of traditional structures using four real-world datasets. The experimental results show that our NP-LSTM hybrid model obtains superior performance in various metrics for time series forecasting. © 2022 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

NOMABER: A Novel Framework for Multi-Type Abnormal Behaviour Recognition

NOMABER: A Novel Framework for Multi-Type Abnormal Behaviour...

引用

2022 IEEE International Conference on Big Data, Big Data 2022

作者： Wang, Ao Yao, Yongchen Yao, Yuhan Chen, Jinpeng Beijing University of Posts and Telecommunications School of Computer Science National Pilot Software Engineering School Beijing China

ISBN: (纸本)9781665480451

Recently, using machine learning technology to realize abnormal behavior recognition in video surveillance to replace human monitoring has become a hot academic topic. In that case, constructing an efficient and unified framework for multi-type abnormal behavior recognition is a worthy topic in machine learning research. This research aims to design a lightweight recognition framework that can recognize various abnormal behaviors in real-time. We propose a Novel framewOrk for the Multi-type Abnormal BEhavior Recognition (NOMABER), which consists of three parts. Firstly, the improved image pre-processing module annotates the abnormal behaviors of image data sets. Secondly, the improved YOLOv5 module is used to identify the multi-type abnormal behaviors, and then the abnormal behaviors are classified by the output module. Finally, experiments on real data sets show that NOMABER is superior to the current methods of real-time performance, identification accuracy, and types of abnormal behaviors. © 2022 IEEE.

关键词： Security systems

来源：评论

学校读者我要写书评

暂无评论

A Stable Task Allocation Method Based on Insertion Operation in Ridesharing

A Stable Task Allocation Method Based on Insertion Operation...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Lv, Jingwei Yao, Shuzhen Tan, Huobin Beihang University School of Computer Science and Engineering Beijing China Beihang University School of Software Beijing China

ISBN: (纸本)9781665465335

In recent years, ridesharing based on mobile Internet has played an important role in public transport services. Ride-hailing platforms have been developed rapidly because of their fully resource utilization of vehicles. In this paper, we propose a task allocation method that satisfies stable matching in ridesharing scenarios, and experiments with real data are carried out to verify the effectiveness of the method. We also compare the effectiveness of this method with the FCFS method. © 2022 IEEE.

关键词： ridesharing single-worker multiple-requesters stable matching

来源：评论

学校读者我要写书评

暂无评论

Named Entity Recognition in Emergency Domain based on BERT-BILSTM-CRF 2

Named Entity Recognition in Emergency Domain based on BERT-B...

引用

2nd IEEE International Conference on Electronic Technology, Communication and Information, ICETCI 2022

作者： Tian, Yu Beijing University of Posts and Telecommunications School of Computer Science National Pilot Software Engineering School Beijing China

ISBN: (数字)9781728181158

ISBN: (纸本)9781728181158

Chinese named entity recognition is a key problem in natural language processing. The traditional language processing model can not effectively represent the context semantic information in the text, and can not deal with the different contexts of polysemy, which affects the effect of entity recognition. A BERT-BILSTM-CRF entity recognition model for the emergency domain is proposed. BERT pre-training language model generates word vectors which represent the semantic information of context, and the generated vectors are characterized by two-way long-term and short-term memory network. Self-attention mechanism can effectively obtain the long-distance dependence in text sentences. And finally, decoding is carried out through the CRF to generate an entity label sequence. The experimental results show that the model have achieved excellent results in the emergency domain corpus. © 2022 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

A Code Completion Approach Combining Pointer Network and Transformer-XL Network 19th

A Code Completion Approach Combining Pointer Network and Tr...

引用

19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Zhang, Xiangping Liu, Jianxun Long, Teng Hu, Haize School of Computer Science and Engineering Hunan University of Science and Technology Hunan Xiangtan411100 China Hunan Key Lab. for Services Computing and Novel Software Technology Hunan University of Science and Technology Hunan Xiangtan411100 China

ISBN: (纸本)9783031545207

Code completion is an integral component of modern integrated development environments, as it not only facilitates the software development process but also enhances the quality of software products. By leveraging large-scale codes to learn the probability distribution among code token units, deep learning methods have demonstrated significant improvements in the accuracy of token unit recommendations. However, the effectiveness of code completion with deep learning techniques is hindered by information loss. To alleviate the above problem, we proposed a code language model which combines the pointer network and Transformer-XL network to overcome the limitations of existing approaches in code completion. The proposed model takes as input the original code fragment and its corresponding abstract syntax tree and leverages the Transformer-XL model as the basis model for capturing long-term dependencies. Furthermore, we integrate a pointer network as a local component to predict the out-of-vocabulary words. The proposed method is evaluated on real PY150 and JS150 datasets. The comparative experimental results demonstrate the effectiveness of our model in improving the accuracy of the code completion task at the token unit level. © ICST Institute for computer sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Probability distributions

来源：评论

学校读者我要写书评

暂无评论

FL-GNN: Efficient Fusion of Fuzzy Neural Network and Graph Neural Network 27

FL-GNN: Efficient Fusion of Fuzzy Neural Network and Graph N...

引用

27th European Conference on Artificial Intelligence, ECAI 2024

作者： Du, Boyu Zhou, Jingya Liu, Ling She, Xiaolong School of Computer Science and Technology Soochow University China Engineering Lab.of Big Data and Intelligence of Jiangsu Province Soochow University China State Key Lab.for Novel Software Technology Nanjing University China School of Computer Science Georgia Institute of Technology United States

ISBN: (纸本)9781643685489

Graph Neural Networks (GNNs) have become an important graph feature learning paradigm that is extensively applied to graph inference ***, GNNs still have limitations in some aspects such as representation capability, interpretability, *** this end, this paper introduces a novel hybrid Fuzzy-Logic Graph Neural Network (FL-GNN) that synergistically combines Fuzzy Neural Network (FNN) and GNN to effectively capture and aggregate local information flows within the ***-GNN exhibits three distinctive ***, we incorporate a specialized structure fuzzy rule to enhance FL-GNN's graph inference capability, surpassing representative GNN ***, we augment the interpretability of FL-GNN by integrating analytical exploration methods from two perspectives: Fuzzy Inference System and Message Passing Algorithm (MPA).Lastly, we refine the structure of FL-GNN based on MPA to optimize its calculation complexity and consequently improve learning *** results show that FL-GNN outperforms existing representative graph neural networks for graph inference tasks. © 2024 The Authors.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Open Source software Supply Chain Recommendation Based on Heterogeneous Information Network 14th

Open Source Software Supply Chain Recommendation Based on H...

引用

14th International Symposium on Benchmarking, Measuring, and Optimization, Bench 2022

作者： Lin, HaiMing Liang, Guanyu Wu, Yanjun Wu, Bin Tian, Chunqi Wang, Wei Nanjing Institute of Software Technology Nanjing211135 China School of Computer and Science Tongji University Shanghai201804 China Institude of Software Chinese Academy of Science Beijing100190 China School of Data Science and Engineering East China Normal University Shanghai200062 China

ISBN: (纸本)9783031311796

In the GitHub open-source collaborative development scenario, each entity type and the link relationship between them have natural heterogeneous attributes. In order to improve the accuracy of project recommendation, it is necessary to effectively integrate this multi-source information. Therefore, for the project recommendation scenario, this paper defines an open source weighted heterogeneous information network to represent the different entity types and link relationships in the GitHub open source collaborative development scenario, and effectively model the complex interaction among developers, projects and other entities. Using the weighted heterogeneous information network embedding method, extract and use the rich structural and semantic information in the weighted heterogeneous open source information network to learn the node representation of developers and projects, and fuse the personalized nonlinear fusion function into the matrix decomposition model for open source project recommendation. Finally, this paper makes a large number of comparative experiments based on the real GitHub open data set, and compares it with other project recommendation methods to verify the effectiveness of our proposed open source project recommendation model. At the same time, it also explores the impact of different metapaths on the effect of project recommendation. The experimental results show that the recommendation method based on heterogeneous information network can effectively improve the recommendation quality. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Open source software

来源：评论

学校读者我要写书评

暂无评论

Conflict-Free Genetic Algorithm with Nash Equilibrium Seeking for Game-Based Battery Swapping Station Recommendation

Conflict-Free Genetic Algorithm with Nash Equilibrium Seekin...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Sun, Chang-Long Xu, Xin-Xin Chen, Chun-Hua Hong, Jun He, Zhenan Yu, Dengxiu Kwong, Sam Zhan, Zhi-Hui School of Computer Science and Engineering South China University of Technology Guangzhou510006 China School of Computer Science and Technology Ocean University of China Qingdao266100 China School of Software Engineering South China University of Technology Guangzhou510006 China College of Computer Science Sichuan University Chengdu China School of Artificial Intelligence Northwestern Polytechnical University Xi'an China Lingnan University Department of Computing and Decision Science Hong Kong College of Artificial Intelligence Nankai University Tianjin300350 China

ISBN: (纸本)9781665410205

The rapid growth of electric vehicles (EVs) has led to significant challenges in providing efficient and sustainable charging solutions. This paper addresses the battery swapping station (BSS) recommendation problem by proposing a novel conflict-free genetic algorithm (CFGA) integrated with a Nash equilibrium seeking (NES) approach to identify optimal Nash equilibrium (ONE) solutions to such a non-cooperative optimization problem. The CFGA employs specialized crossover and mutation operators to generate offspring that satisfy the constraints of the problem, ensuring that each EV decides a unique battery swap strategy without conflict. Firstly, an order crossover operator is proposed to preserve the order of genes in the chromosomes. Secondly, a replacement and exchange mutation operator is proposed to enhance mutation diversity. The resulting optimal solution is then used as the initial strategy for the NES, which iteratively converges to the ONE. The proposed CFGA with NES algorithm is evaluated under both small-scale and large-scale cases, demonstrating its effectiveness in achieving a balance between costs for EVs and utilization for BSSs. The study's findings have practical implications for the smart grid and EV integration, offering a robust method for optimizing EV infrastructure and operations. © 2024 IEEE.

关键词： Charging stations

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：