International Conference on Algorithms, Microchips and Network Applications最新文献_第8页

Evolution simulation of spatial spillover effect of carbon emission efficiency based on improved PSO-PFCM clustering algorithm 基于改进的 PSO-PFCM 聚类算法的碳排放效率空间溢出效应演化模拟

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3032126

Yufeng Chai, Yuehua Li, Bing Cai, Liang Han, Jiangbo Sha

{"title":"Evolution simulation of spatial spillover effect of carbon emission efficiency based on improved PSO-PFCM clustering algorithm","authors":"Yufeng Chai, Yuehua Li, Bing Cai, Liang Han, Jiangbo Sha","doi":"10.1117/12.3032126","DOIUrl":"https://doi.org/10.1117/12.3032126","url":null,"abstract":"By simulating and analyzing the spatial spillover effect between different regions, the spatial correlation of carbon emission efficiency can be studied. Understanding how carbon emission behaviors interact and transmit across regions will help to develop more comprehensive and accurate carbon emission management strategies. Therefore, a new evolutionary simulation method for spatial spillover effect of carbon emission efficiency is proposed in this study. The PSO-PFCM clustering algorithm was improved to detect the overflow of carbon emission efficiency. The main characteristics of the multidimensional spatial spillover effect of carbon emission efficiency were selected, the multidimensional spatial feature mapping model was constructed, and the level of spillover effect was judged to complete the analysis of the evolution of the spatial spillover effect of carbon emission efficiency. The experimental results show that the proposed method has shorter abnormal detection time of carbon emission data spill and higher evolutionary accuracy of spatial spillover effect of carbon emission efficiency.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141369152","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

Design of indoor formaldehyde multipoint real-time monitoring and alarm system 室内甲醛多点实时监测和报警系统的设计

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3032076

Xuexiao Chen

引用次数: 0

Research on haze prediction method of Xianyang City based on STL decomposition and FEDformer 基于 STL 分解和 FEDformer 的咸阳市雾霾预测方法研究

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3031964

Yanan Cao, Qian Zhou, Jinglei Tang, Zhenhong Liu

{"title":"Research on haze prediction method of Xianyang City based on STL decomposition and FEDformer","authors":"Yanan Cao, Qian Zhou, Jinglei Tang, Zhenhong Liu","doi":"10.1117/12.3031964","DOIUrl":"https://doi.org/10.1117/12.3031964","url":null,"abstract":"Due to the continuous impact of haze weather, Xianyang city's air quality has ranked in the bottom three of the province for three consecutive years. This has led to an urgent need to improve air quality. Haze pollution prediction is of great practical significance. By timely and accurate prediction of haze pollution, the government and relevant institutions can take necessary measures to improve air quality and protect the ecosystem. Although the traditional RNN and LSTM models can effectively capture the time sequence information in the haze data over the years for prediction, it is still difficult to achieve accurate prediction due to the complexity of haze prediction. In this study, 8769 pieces of heterogeneous data were successfully collected using multi-source big data acquisition technology. A series of pre-processing operations, including data conversion and dimensionality reduction, were performed on different data such as AQI, PM2.5, PM10, SO2, NO2, CO and O3. The method of big data fusion and deep learning is adopted to integrate haze data and discover hidden rules and trends in it. Finally, based on FEDformer model and STL time series decomposition method, the prediction model was established in this study, which achieved significant improvement in both short - and long-term time series prediction problems.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141370327","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

Advanced deep-learning-based chip design enabling algorithmic and hardware architecture convergence 基于深度学习的先进芯片设计实现了算法和硬件架构的融合

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3032069

Hedi Qu, Danqing Ma, Zongqing Qi, Ni Zhu

引用次数: 0

Research on secure and trustworthy cross domain collaborative computing methods for data 研究安全可信的跨域数据协作计算方法

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3032067

Xinlin Liu, Jian Zhang, Wei-Ping Deng

{"title":"Research on secure and trustworthy cross domain collaborative computing methods for data","authors":"Xinlin Liu, Jian Zhang, Wei-Ping Deng","doi":"10.1117/12.3032067","DOIUrl":"https://doi.org/10.1117/12.3032067","url":null,"abstract":"With the advancement of mobile cloud computing technology, the demand for collaborative operation and maintenance technology is constantly increasing. Therefore, this article proposes a model that combines multi feature collaborative knowledge graph and blockchain technology to achieve secure and trustworthy collaborative operation and maintenance computing in cross domain environments. The model focuses on addressing data privacy and security issues, and improving the accuracy of collaborative operations. By introducing a multi feature collaborative knowledge graph, secure fusion of multi-source feature data can be achieved. Meanwhile, design a blockchain based trust verification mechanism to ensure the traceability of anonymous data sources, prevent data tampering, and ensure data authenticity. In addition, an adaptive recommendation algorithm based on MKGCN is proposed, which utilizes multi feature collaborative knowledge graph data to achieve secure and accurate collaborative computing. The experimental results show that this method improves the accuracy of recommendation calculation while ensuring privacy and security, promoting the development and practical application of cross domain operation and maintenance computing technology.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141368864","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

GNAR: graph contrastive learning networks with adaptive readouts for anomaly detection GNAR：带有自适应读数的图形对比学习网络，用于异常检测

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3031986

changcheng wan, Suixiang Gao

引用次数: 0

LDA-Bert based public opinion subject mining analysis of emergencies 基于LDA-Bert的突发事件舆情主体挖掘分析

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2023-05-08 DOI: 10.1117/12.2679263

Tiantian Liu, XIAO-FENG Gu

引用次数: 0

Study on emergency logistics location-route problem under uncertain demand 需求不确定条件下应急物流选址路线问题研究

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2023-05-08 DOI: 10.1117/12.2679063

Qirong Li

引用次数: 0

An intelligent algorithm integrated with fit algorithms for solving the one-dimensional bin packing problem under multiple length restrictions 结合拟合算法求解多长度约束下的一维装箱问题

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2023-05-08 DOI: 10.1117/12.2679127

Kancheng Huang, Yueming Dai

引用次数: 0

RGB-T object tracking with adaptive decision fusion 基于自适应决策融合的RGB-T目标跟踪

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2023-05-08 DOI: 10.1117/12.2679107

Yida Bai, Ming Yang

{"title":"RGB-T object tracking with adaptive decision fusion","authors":"Yida Bai, Ming Yang","doi":"10.1117/12.2679107","DOIUrl":"https://doi.org/10.1117/12.2679107","url":null,"abstract":"Visual object tracking is a traditional task in computer vision, which has developed with several decades. With the development of machine learning, Correlation Filter (CF) has been proposed with satisfying performance and very high framerate. Though the CF framework has numerous strengths in this task, the tracker is fragile to miss the target in several scenes, including extreme illumination, target occlusion and deformation. Recently, thermal modality, which detects the target’s temperature, is robust to the night scenes and can provide a precise target contour. In this paper, we propose a CF based tracker with decision fusion strategy for visible-thermal (RGB-T) tracking. First, we introduce multi-modal KCF trackers as our baseline. Then, we design a decision fusion method considering the Peak-to-Side Rate (PSR) of the score maps, thereby achieving an adaptive fusing those modalities and avoiding model’s heterogeneity. In the experiments, our tracker has validated on the public dataset, namely GTOT. Compared with two uni-modality trackers, the proposed tracker with real-time speed has shown superior results on both target localization and scale estimation.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121169838","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