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IEEE International Conference on Big data Analysis (ICBDA)

作者： Rong Hu Ye Xia Chih-Yu Hsu Hanlin Chen Weihui Xu Fujian Provincial Key Laboratory of Automotive Electronics and Electric Drive Fujian University of Technology Fuzhou China School of Ecological Environment and Urban Construction Fujian University of Technology Fuzhou China School of Information Science and Engineering Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications National Demonstration Center Fuzhou China

ISBN: (数字)9781728141114

ISBN: (纸本)9781728141121

The autonomous vehicle navigation system and the intelligent traffic system need real-time routing planning in traffic engineering and management. Urban road intersections play bottlenecks of urban roads, contributing a great deal to the loss of travel time due to traffic interference, management and control. The detection of the traffic intersection is important for obtaining real-time road regulation information. This paper proposes a method to detect the traffic intersection based on floating car data that is typically timestamped geo-localization, direction and speed data directly collected by moving vehicles. The angle of the direction difference can be used as the features for detecting the traffic intersection. The identification of the traffic intersections algorithm is developed based on the data density clustering algorithm. The floating car data is collected by about 15,000 cars using an onboard with the Global Positioning System receiver and sensors that providing positions (latitude, longitude) instantaneous speed, drive direction and time etc. The assessment results show the approach has excellent performance with high accuracy for traffic intersection detection.

关键词： Automobiles Trajectory Roads Clustering algorithms Turning Real-time systems Urban areas

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Prevention of external force damage to overhead power lines based on network and intelligent positioning

Journal of Network Intelligence

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Journal of Network Intelligence 2021年第3期6卷 551-583页

作者： Xie, Bo-Lin Pan, Jeng-Shyang Lin, Yuh-Chung Xie, Yu-Hong Pan, Tien-Szu Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China School of Information Science and Technology Sanda University Shanghai201209 China Guangdong Power Grid Heyuan Power Supply Bureau Transmission Management Office China Southern Power Grid Heyuan517000 China Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung807 Taiwan

In the research on the prevention of external damage to power transmission lines, it is a difficult problem to prevent large machinery vehicles from damaging the overhead transmission lines. After the emergence of video surveillance technology, the accident rate has dropped significantly. But still unable to completely eliminate such accidents. The anti-external damage solution based on network and intelligent positioning is very effective for early warning of accidents. This gives us the opportunity to completely eliminate such accidents. In this paper we utilize the satellite positioning data of the power towers to establish a warning zone along the power line. When the system detects that some large machinery vehicles enter the warning zone, early warning messages will be sent to these vehicles. Afterward, the connection between vehicle drivers and management center can be established such that further instructions can be ordered to avoid accidents. According to our simulations, it presents our proposed mechanism can effectively prevent the damage occurrences which may be caused by large machinery vehicles. © 2021 Journal of Network Intelligence.

关键词： Accidents

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Rethinking Lightweight Convolutional Neural Networks for Efficient and High-quality Pavement Crack Detection

arXiv

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arXiv 2021年

作者： Li, Kai Yang, Jie Ma, Siwei Wang, Bo Wang, Shanshe Tian, Yingjie Qi, Zhiquan School of Computer Science Institute of Digital Media Peking University Beijing100871 China School of Mathematics Sciences University of Chinese Academy of Sciences Beijing100049 China Advanced Institute of Information Technology Peking University Hangzhou310005 China School of Information Technology and Management University of International Business and Economics Beijing100029 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation University of Chinese Academy of Sciences No. 3 South Yitiao Zhongguancun Haidian District Beijing100190 China

Pixel-level road crack detection has always been a challenging task in intelligent transportation systems. Due to the external environments, such as weather, light, and other factors, pavement cracks often present low contrast, poor continuity, and different sizes in length and width. However, most of the existing studies pay less attention to crack data under different situations. Meanwhile, recent algorithms based on deep convolutional neural networks (DCNNs) have promoted the development of cutting-edge models for crack detection. Nevertheless, they usually focus on complex models for good performance, but ignore detection efficiency in practical applications. In this article, to address the first issue, we collected two new databases (i.e. Rain365 and Sun520) captured in rainy and sunny days respectively, which enrich the data of the open source community. For the second issue, we reconsider how to improve detection efficiency with excellent performance, and then propose our lightweight encoder-decoder architecture termed CarNet. Specifically, we introduce a novel olive-shaped structure for the encoder network, a light-weight multi-scale block and a new up-sampling method in the decoder network. Numerous experiments show that our model can better balance detection performance and efficiency compared with previous models. Especially, on the Sun520 dataset, our CarNet significantly advances the state-of-the-art performance with ODS F-score from 0.488 to 0.514. Meanwhile, it does so with an improved detection speed (104 frame per second) which is orders of magnitude faster than some recent DCNNs-based algorithms specially designed for crack detection. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

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Concatenated Attention Neural Network for Image Restoration

arXiv

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arXiv 2020年

作者： Tian, YingJie Wang, YiQi Yang, LinRui Qi, ZhiQuan School of Economics and Management University of Chinese Academy of Sciences Beijing China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China School of Computer Science Technology University of Chinese Academy of Sciences Beijing China Sino-Danish College University of Chinese Academy of Sciences China

In this paper, we present a general framework for low-levelvision tasks including image compression artifacts reduction and image denoising. Under this framework, a novel concatenated attention neural network (CANet) is specifically designed for image restoration. The main contributions of this paper are as follows: First, by applying concise but effective concatenation and feature selection mechanism, we establish a novel connection mechanism which connect different modules in the modules stacking network. Second, both pixel-wise and channel-wise attention mechanisms are used in each module convolution layer, which promotes further extraction of more essential information in images. Lastly, we demonstrate that CANet achieves better results than previous state-of-the-art approaches with sufficient experiments in compression artifacts removing and image denoising. Copyright © 2020, The Authors. All rights reserved.

关键词： Feature extraction

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Extremely Short Chinese Text Classification Method Based on Bidirectional Semantic Extension

Extremely Short Chinese Text Classification Method Based on ...

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作者： Yongzeng Yue Yuhong Zhang Xuegang Hu Peipei Li Key Laboratory of knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education School of Computer Science and Information Engineering Hefei University of Technology

Short text classification methods have achieved significant progress and wide application on text data such as Twitter and Weibo. However, the extremely short chinese texts like tax invoice data are different with traditional short texts in lackness of contextual semantic information, feature sparseness and extremely short length. The existing short text classification methods are difficult to achieve a satisfactory performance in these texts. To address these problems, this paper proposes a text classification method based on bidirectional semantic extension for extremely short texts like Chinese tax invoice data. More specifically, firstly, the Chinese knowledge graph is introduced for extending bidirectional semantic of texts and label data to expand the extremely short texts and ease the problem of feature sparseness;secondly,the hash vectorization is used to avoid the semantic problem caused by the lackness of contextual information. Experimental results conducted the real tax invoice dataset demonstrate the effectiveness of our proposed method.

关键词： Extremely Short Chinese Text Classification Method Based on Bidirectional Semantic Extension

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Mapping the distribution of pine wilt disease based on selected machine learning algorithms and high-resolution Gaofen-2/7 remote sensing

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International Journal of Digital Earth 2025年第1期18卷

作者： Yifan Wang Xiaocheng Zhou Chongcheng Chen Xiaoqin Wang Hao Wu Fanglin Tan Ruijiao Wu a Local Joint Engineering Research Center of Satellite Geospatial Information Technology Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education Fuzhou University Fuzhou People’s Republic of China b East China Inventory and Planning Institute National Forestry and Grassland Administration(NFGA) Hangzhou People’s Republic of China c Fujian Academy of Forestry Fuzhou People’s Republic of China d Fujian Geological Surveying and Mapping Institute Fuzhou China

ABSTRACTUnder the influence of human activities and climate change, pine wilt disease (PWD) has caused significant damage to Masson’s pine (Pinus massonianaLamb.) forests in subtropical China. Existing research has struggled to accurately capture the large-scale spatial distribution of the PWD, particularly for precise extraction at provincial level. This study focuses on Fujian province and proposes a novel method for extracting PWD information at the sub-stand level. This approach uses forest age, canopy height, and temporal vegetation indices (VIs) data for deadwood distribution sub-stands to identify the suspected outbreak areas. In key counties and cities, High-resolution satellite imagery (GF-2 and GF-7) was used to construct a bi-level scale-set model (BSM) for efficient image segmentation, followed by selection of the best classification algorithm for data extraction. For non-key counties, sentinel imagery with 10-meter resolution was used on the GEE cloud platform with RF classification. The results showed an overall annual extraction accuracy exceeding 90%, and statistical analysis revealed a significant reduction in the number of dead trees from 2021 to 2022, indicating effective control measures. This study demonstrated that multi-source remote sensing data can efficiently extract PWD distribution information, fill data gaps for provincial-level monitoring, and support forest pest management.

关键词： Pine wilt disease remote sensing meter-scale resolution imagery bi-level scale-set model sentinel imagery

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Corrigendum to “Weak multi-label learning with missing labels via instance granular discrimination” [Inform. Sci. 594 (2022) 200–216]

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Information Sciences 2023年 619卷 1-1页

作者： Anhui Tan Xiaowan Ji Jiye Liang Yuzhi Tao Wei-Zhi Wu Witold Pedrycz School of Information Engineering Zhejiang Ocean University Zhoushan Zhejiang 316022 PR China School of Computer and Information Technology Shanxi University Taiyuan 030006 Shanxi PR China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhoushan Zhejiang 316022 PR China Department of Electrical and Computer Engineering University of Alberta Edmonton T6R 2V4 AB Canada

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Study on the Relationships between Utilization Ratios and Conversion Rates of Nitrogen,Phosphorus and Potassium for Wheat

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Meteorological and Environmental Research 2020年第5期11卷 46-54页

作者： Zhiping HUANG Xianda HOU Shutian LIU Shuojin WANG Hongyan ZHENG Jian DING Changhong MI Ling LU Yanlin HOU Agro-Environmental Protection Institute Ministry of Agriculture and Rural AffairsTianjin 300191China Guangxi Geographical Indication Crops Research Center of Big Data Mining and Experimental Engineering Technology Nanning Normal UniversityNanning 530001China Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation Nanning Normal UniversityNanning 530001China Key Laboratory of Environment Change and Resources Use in Beibu Gulf(Nanning Normal University) Nanning 530001China

This paper studied the relationships between utilization ratios and conversion rates of nitrogen,phosphorus and potassium for wheat by data mining method based on data of"3414 fertilizer field trials"of wheat by published papers from national soil testing and recommendation since *** results and conclusions were as follows:①the conceptual model of fertilizer utilization ratio of wheat for plot was that,Y N≈a+b×optimum nitrogen application amount+c×optimum fertilizer amount of K+d×rainfall in growth season,Y P≈a+b×optimum fertilizer amount of K+c×rainfall in growth season,Y K≈a+b×temperature in growth season+c×rainfall in growth season-d×optimum yield-e×optimum nitrogen application amount,respectively.②Fertilizer utilization ratio and nutrient conversion rate had 4 kinds of *** significant relationships:13,of which 8 were soil nutrients,the results showed that soil nutrients had little effect on nutrient conversion rate and fertilizer utilization ratio;consistent significant relationships:4,they were all nitrogen and phosphorus,explaining the importance of nitrogen and phosphorus;contrary significant relationships:6,they were all nitrogen and phosphorus,illustrating that phosphorus and nitrogen had inhibitory effect;complementary significant relationships:31,the cause of the complementary phenomenon was that the fertilizer utilization ratio was the measuring index of fertilizer efficiency in one season,while the nutrient conversion rate was the measuring index of fertilizer efficiency in more *** showed that the fertilizer utilization rate was significantly correlated,or the nutrient conversion rate was significantly correlated.

关键词： Optimum yield Optimum fertilization amount Nutrient conversion rate Fertilizer utilization ratio Relative abundance-deficiency value of soil nutrient

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Specific Index System of Ecological Balanced Fertilization for Wheat

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Meteorological and Environmental Research 2020年第5期11卷 38-45页

作者： Zhiping HUANG Ling LU Shutian LIU Shuojin WANG Xianda HOU Hongyan ZHENG Jian DING Changhong MI Yanlin HOU Agro-Environmental Protection Institute Ministry of Agriculture and Rural AffairsTianjin 300191China Guangxi Geographical Indication Crops Research Center of Big Data Mining and Experimental Engineering Technology Nanning Normal UniversityNanning 530001China Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation Nanning Normal UniversityNanning 530001China Key Laboratory of Environment Change and Resources Use in Beibu Gulf(Nanning Normal University) Nanning 530001China

This paper studied the index system of ecological balanced fertilization for wheat by data mining method based on data of"3414 fertilizer field trials"of wheat by published papers from national soil testing and recommendation since *** results and conclusions were as follows.①Soil nutrient content could not be used as indicator of fertilizer application of wheat.②The conceptual model of N utilization ratio of wheat for plot was Y N≈a+b×optimum production-c×optimum fertilizer amount of N-d×temperature in growing season-e×rainfall in growing season,and the conceptual model of P conversion rate was Y P≈a+b×optimum production+c×temperature in growing season+d×precipitation in growing season-e×optimum fertilizer amount of P-f×optimum fertilizer amount of K,and the conceptual model of K conversion rate of wheat plots was that,Y K≈a-b×optimum fertilizer amount of K.③The conceptual model of the optimum fertilizer amount of N of wheat for plot was Y N≈a+b×optimum production+c×optimum fertilizer amount of P-d×temperature in growing season-e×rainfall in growing season,and the conceptual model of the optimum fertilizer amount of P was Y P≈a+b×optimum production+c×optimum fertilizer amount of N+d×optimum fertilizer amount of K,and the conceptual model of the optimum fertilizer amount of K was Y K≈a+b×optimum fertilizer amount of P.④The conceptual model of relative abundance-deficiency value of soil N of wheat for plot was that Y N≈a-b×temperature in growing season-c×precipitation in growing season,and the conceptual model of relative abundance-deficiency value of soil P was Y P≈a+b×optimum yield+c×optimum fertilizer amount of N+d×precipitation in growing season-e×optimum fertilizer amount of K,and the conceptual model of relative abundance-deficiency value of soil K was Y K≈a+b×optimum yield+c×optimum fertilizer amount of K.

关键词： Optimum yield Optimum fertilization amount Nutrient conversion rate Fertilizer utilization ratio Relative abundance-deficiency value of soil nutrient

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Research and Application of Prediction Model for Ecological Balanced Optimal Fertilization Amount for Three Crops

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Meteorological and Environmental Research 2020年第5期11卷 96-103页

作者： Zhiping HUANG Shutian LIU Xianda HOU Shuojin WANG Hongyan ZHENG Jian DING Changhong MI Ling LU Yanlin HOU Agro-Environmental Protection Institute Ministry of Agriculture and Rural AffairsTianjin 300191China Guangxi Geographical Indication Crops Research Center of Big Data Mining and Experimental Engineering Technology Nanning Normal UniversityNanning 530001China Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation Nanning Normal UniversityNanning 530001China Key Laboratory of Environment Change and Resources Use in Beibu Gulf(Nanning Normal University) Nanning 530001China

This paper analyzed the modeling principle,process and application process of the new ecological balanced fertilization model by data mining method based on the relationships among soil abundance-deficiency index,optimum fertilization amount and nutrient conversion rate of N,P,K for rice,wheat and maize in column *** results and conclusions were as follows:①on the basis of two ecological balanced fertilization models(available and total nutrients),a prediction model system of optimum fertilization amount based on nutrient conversion rate was established,including 3 *** first model predicted the optimum fertilization amount based on nutrient conversion rate,and the second model determined prediction difference value of optimum fertilization amount in the first amendment based on optimum yield,and the third model determined prediction difference value of optimum fertilization amount in the second amendment based on nutrient conversion rate.②Nutrient conversion rate and optimum yield were the common parameters of two models based on contents of available and total nutrients,and they were the core parameters of ecological balanced fertilization *** the specific application,the nutrient conversion rate and optimum yield were determined mainly based on the comprehensive comparison between the regional or similar plot or one plot and the experimental plot.③The two error amendments were due to the use of the fixed nutrient removal of 100 kg seeds,and underestimated the nutrient conversion rate when higher optimum production and overestimated the nutrient conversion rate when lower optimum production.④It was proposed that the nutrient conversion rate was regarded as a comprehensive nutrient index(abundance-deficiency)of ecological balanced *** was not only a parameter to measure fertilizer efficiency,but also a parameter to measure the abundance-deficiency of nutrients,and a parameter to guide fertilization.

关键词： Optimum yield Optimum fertilization amount Nutrient conversion rate Fertilizer utilization ratio Relative abundance-deficiency value of soil nutrient

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