International Journal of Information Technologies and Systems Approach最新文献_第2页

Steel Surface Defect Detection Based on SSAM-YOLO 基于SSAM-YOLO的钢材表面缺陷检测

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-08-18 DOI: 10.4018/ijitsa.328091

Tianle Yang, Jinghui Li

{"title":"Steel Surface Defect Detection Based on SSAM-YOLO","authors":"Tianle Yang, Jinghui Li","doi":"10.4018/ijitsa.328091","DOIUrl":"https://doi.org/10.4018/ijitsa.328091","url":null,"abstract":"The defect inspection of the steel surface is crucial to modern manufacturing and highly depends on inefficient manual work. The emergence of deep learning has prompted the development of automated defect detection methods, but the current methods perform badly in the detection of the crazing and rolled-in scale-two types of defects on steel surfaces. The difficulty in the detection of crazing and rolled-in scale is mainly due to the similarity between object regions and background regions. Based on this, the authors propose a supervised spatial-attention module (SSAM). It introduces a priori knowledge compared to the traditional spatial attention mechanism, which can enhance the supervision of relevant parameters in the attention mechanism module during network training. Finally, they introduced the SSAM to the YOLOv5 and got the SSAM-YOLO. The test result on the NEU-DET dataset shows that the proposed method has better detection accuracy, achieving improvements of 7.3% and 3.02% on the AP@0.5 for the crazing and rolled-in scale. The method also outperforms the comparative main stream algorithms for steel surface defect detection, verifying the effectiveness of our algorithm.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49662588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Is Prompt the Future? 提示是未来吗?

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International Journal of Information Technologies and Systems Approach Pub Date : 2023-08-18 DOI: 10.4018/ijitsa.328681

Zhen Zhu, Liting Wang, Dongmei Gu, Hong Wu, Behrooz Janfada, B. Minaei-Bidgoli

引用次数: 0

Discovery of User Groups Densely Connecting Virtual and Physical Worlds in Event-Based Social Networks 基于事件的社交网络中密集连接虚拟世界和物理世界的用户群体的发现

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International Journal of Information Technologies and Systems Approach Pub Date : 2023-07-28 DOI: 10.4018/ijitsa.327004

Tianming Lan, Lei Guo

{"title":"Discovery of User Groups Densely Connecting Virtual and Physical Worlds in Event-Based Social Networks","authors":"Tianming Lan, Lei Guo","doi":"10.4018/ijitsa.327004","DOIUrl":"https://doi.org/10.4018/ijitsa.327004","url":null,"abstract":"An essential task of the event-based social network (EBSN) platform is to recommend events to user groups. Usually, users are more willing to participate in events and interest groups with their friends, forming a particularly closely connected user group. However, such groups do not explicitly exist in EBSN. Therefore, studying how to discover groups composed of users who frequently participate in events and interest groups in EBSN has essential theoretical and practical significance. This article proposes the problem of discovering maximum k fully connected user groups. To address this issue, this article designs and implements three algorithms: a search algorithm based on Max-miner (MMBS), a search algorithm based on two vectors (TVBS) and enumeration tree, and a divide-and-conquer parallel search algorithm (DCPS). The authors conducted experiments on real datasets. The comparison of experimental results of these three algorithms on datasets from different cities shows that the DCPS algorithm and TVBS algorithm significantly accelerate their computational time when the minimum support rate is low. The time consumption of DCPS algorithm can reach one tenth or even lower than that of MMBS algorithm.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41986134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Analysis of a Power Information Management System Based on Machine Learning Algorithm 基于机器学习算法的电力信息管理系统分析

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International Journal of Information Technologies and Systems Approach Pub Date : 2023-07-28 DOI: 10.4018/ijitsa.327003

Daren Li, Jie Shen, Jiarui Dai, Yifan Xia

{"title":"The Analysis of a Power Information Management System Based on Machine Learning Algorithm","authors":"Daren Li, Jie Shen, Jiarui Dai, Yifan Xia","doi":"10.4018/ijitsa.327003","DOIUrl":"https://doi.org/10.4018/ijitsa.327003","url":null,"abstract":"With the deepening reform of the power market, great progress has been made in informatization. Blockchain can improve the reliability of power management system (PMS) data processing. PMS informatization has become the basis for improving the quality and efficiency of project management and maximizing the social and economic benefits of the project. Due to the requirement of safe and stable power production, PMS attaches great importance to the application and implementation of information in power management, but does not attach enough importance to the informatization of power production management. Therefore, this article analyzes the current situation, characteristics, and existing problems of PMS through a machine learning algorithm, then constructs the design principles, and finally proposes the optimization path of PMS according to the principles. The information collection ability and system control ability of the optimized PMS were better than the original PMS. The information collection ability was 14.2% higher than the original, and the system control ability was 9.8% higher than the original. In general, both blockchain and machine learning can improve the data reliability of PMS.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42737274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluation of Power Grid Social Risk Early Warning System Based on Deep Learning 基于深度学习的电网社会风险预警系统评价

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-07-28 DOI: 10.4018/ijitsa.326933

Daren Li, Jie Shen, Dali Lin, Yangshang Jiang

{"title":"Evaluation of Power Grid Social Risk Early Warning System Based on Deep Learning","authors":"Daren Li, Jie Shen, Dali Lin, Yangshang Jiang","doi":"10.4018/ijitsa.326933","DOIUrl":"https://doi.org/10.4018/ijitsa.326933","url":null,"abstract":"In the context of the continuous development of the power grid, the tasks of regulation, operation, and management are becoming increasingly complex, and the operation risks are also increasing dramatically. Sensor technology can deal with the impact of uncertain risk factors, such as extremely disastrous weather, equipment failure, and load fluctuation, on the power grid. Therefore, this article proposes a real-time risk analysis and early warning system for the power grid based on machine learning and combined with sensing technology—a stack self-coding (SSC) neural network prediction model—and introduces the functional composition of the system, clarifying the research content. The experiment compared the accuracy of power grid load forecasting between the SSC forecasting model and the fuzzy neural network (FNN) forecasting model and obtained the forecasting curves of a holiday, a workday, and a Sunday, as well as a comprehensive forecasting accuracy comparison. The experimental results showed that the SSC prediction model based on machine learning designed in this paper improved the prediction accuracy by 12.94% compared with the FNN model. The power grid risk can be assessed through load forecasting, and it is also of great significance for load dispatching and reducing generation costs.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45485341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robot Path Planning Method Combining Enhanced APF and Improved ACO Algorithm for Power Emergency Maintenance 基于改进型有源电力滤波器和改进型ACO算法的电力抢修机器人路径规划方法

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-07-24 DOI: 10.4018/ijitsa.326552

Wei Wang, Xiaohai Yin, Shiguang Wang, Jianmin Wang, Guowei Wen

引用次数: 0

Forecasting Model of Electricity Sales Market Indicators With Distributed New Energy Access 分布式新能源接入下的电力销售市场指标预测模型

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-07-21 DOI: 10.4018/ijitsa.326757

Tao Yao, Xiaolong Yang, Chenjun Sun, Peng Wu, Shuqian Xue

{"title":"Forecasting Model of Electricity Sales Market Indicators With Distributed New Energy Access","authors":"Tao Yao, Xiaolong Yang, Chenjun Sun, Peng Wu, Shuqian Xue","doi":"10.4018/ijitsa.326757","DOIUrl":"https://doi.org/10.4018/ijitsa.326757","url":null,"abstract":"It is difficult for the existing electricity sales market to adapt to the vast amount of distributed new energy access. This article proposes an electricity sales market index prediction model for high proportion distributed new energy access under the cloud-side cooperation architecture. First, an index prediction system is designed based on the cloud edge collaboration architecture. The edge computing center processes regional data nearby to improve prediction efficiency. Second, on the edge side, a K-means clustering algorithm is used to classify the data. Third, the power data, distributed power output data, load data, weather data, holiday information, and electricity price data are obtained. Finally, the ConvLSTM-Adaboost prediction model is built in the cloud center. The ConvLSTM is used as the base learner, and the Adaboost-integrated algorithm is used for serial training. At the same time, the prediction results of each base learner are weighted and integrated to obtain the final power and load prediction results of the electricity sales market. Experiments show that the prediction results of MAE, PMSE, and MAPE of the proposed model for daily electricity are 52.539MW, 56.859MW, and 2.063%, respectively. Not only is this superior to other models, but it provides a better analysis of influencing factors.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48124289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Health Assessment Method of Equipment in Distribution Court Based on Big Data Analysis in the Framework of Distribution Network of Things 物联网配电网框架下基于大数据分析的配电网设备健康评估方法

IF 0.8

International Journal of Information Technologies and Systems Approach Pub Date : 2023-07-21 DOI: 10.4018/ijitsa.326755

Long Su, K. Wang, Qiaochu Liang, Lifeng Zhang

{"title":"Health Assessment Method of Equipment in Distribution Court Based on Big Data Analysis in the Framework of Distribution Network of Things","authors":"Long Su, K. Wang, Qiaochu Liang, Lifeng Zhang","doi":"10.4018/ijitsa.326755","DOIUrl":"https://doi.org/10.4018/ijitsa.326755","url":null,"abstract":"Focusing on the problem that the quantity of equipment in the distribution court is huge and the operation status is difficult to reliably control, a method of equipment health status assessment in the distribution court based on big data analysis in the distribution network of things architecture is proposed. Firstly, based on the internet of things for power distribution, the evaluation system of equipment status in the distribution court is designed to ensure the efficient analysis of massive data through the cooperation of cloud center and edge computing. Then, at the edge of the system, the grey correlation analysis algorithm and the Granger hypothesis method are used to obtain the correlation and causality of the failure rate of equipment components and the influencing factors so as to understand the accurate failure rate of equipment components. Finally, the weight of factors affecting the equipment failure rate is identified by using the dynamic variable weight analytic hierarchy process, and it is corrected in the cloud center; and the overall health degree of the equipment in the distribution court is obtained through transformation. Based on the selected station area model, the proposed method is experimentally demonstrated. The results show that it can accurately obtain the real-time health status of the court equipment and the evaluation accuracy is close to 98%, which provides theoretical support for the operation and maintenance of the distribution network.","PeriodicalId":52019,"journal":{"name":"International Journal of Information Technologies and Systems Approach","volume":" ","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43291621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring Enhancement of AR-HUD Visual Interaction Design Through Application of Intelligent Algorithms 探索应用智能算法增强AR-HUD视觉交互设计

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International Journal of Information Technologies and Systems Approach Pub Date : 2023-07-21 DOI: 10.4018/ijitsa.326558

Jian Teng, Fucheng Wan, Yiquan Kong

引用次数: 0

Manipulator Control Based on Adaptive RBF Network Approximation 基于自适应RBF网络逼近的机械手控制

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International Journal of Information Technologies and Systems Approach Pub Date : 2023-07-21 DOI: 10.4018/ijitsa.326751

Xindi Yuan, Mengshan Li, Qiusheng Li

引用次数: 0