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Lin He, Shengnan Wang and Xinran Cao
Shipping Enterprise Credit Named Entity Recognition (NER) aims to recognize shipping enterprise credit entities from unstructured shipping enterprise credit texts. Aiming at the problem of low entity recognition rate caused by complex and diverse entitie...
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Yongsheng Yang, Zhongtao He, Haiqing Yao, Yifei Wang, Junkai Feng and Yuzhen Wu
Due to their unique structural design, portal cranes have been extensively utilized in bulk cargo and container terminals. The bearing fault of their drive motors is a critical issue that significantly impacts their operational efficiency. Moreover, the ...
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Yuan Chen and Abdul Q. M. Khaliq
The Lee?Carter model could be considered as one of the most important mortality prediction models among stochastic models in the field of mortality. With the recent developments of machine learning and deep learning, many studies have applied deep learni...
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Yong Fang, Shaoshuai Yang, Bin Zhao and Cheng Huang
With the propagation of cyberbullying in social networks as a trending subject, cyberbullying detection has become a social problem that researchers are concerned about. Developing intelligent models and systems helps detect cyberbullying automatically. ...
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Wenkuan Li, Peiyu Liu, Qiuyue Zhang and Wenfeng Liu
Text sentiment analysis is an important but challenging task. Remarkable success has been achieved along with the wide application of deep learning methods, but deep learning methods dealing with text sentiment classification tasks cannot fully exploit s...
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Pengpeng Li, An Luo, Jiping Liu, Yong Wang, Jun Zhu, Yue Deng and Junjie Zhang
Chinese address element segmentation is a basic and key step in geocoding technology, and the segmentation results directly affect the accuracy and certainty of geocoding. However, due to the lack of obvious word boundaries in Chinese text, the grammatic...
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Sanjiban Sekhar Roy, Ali Ismail Awad, Lamesgen Adugnaw Amare, Mabrie Tesfaye Erkihun and Mohd Anas
In today?s world, phishing attacks are gradually increasing, resulting in individuals losing valuables, assets, personal information, etc., to unauthorized parties. In phishing, attackers craft malicious websites disguised as well-known, legitimate sites...
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Zulfiqar Ahmad Khan, Amin Ullah, Waseem Ullah, Seungmin Rho, Miyoung Lee and Sung Wook Baik
Smart grid technology based on renewable energy and energy storage systems are attracting considerable attention towards energy crises. Accurate and reliable model for electricity prediction is considered a key factor for a suitable energy management pol...
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Feng Wang, Hongbo Lin and Ziming Ma
Aiming to improve on the low accuracy of current transmission line icing prediction models and ignoring the objective law of icing of transmission lines, a transmission line icing prediction model considering the effect of transmission line tension on th...
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Yibo Liu, Qingyun Zuo, Xu Wang and Teng Zong
Entity relation extraction mainly extracts relations from text, which is one of the important tasks of natural language processing. At present, some special fields have insufficient data; for example, agriculture, the metallurgical industry, etc. There i...
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Dongxing Lei, Haijun Liu, Huijun Le, Jianping Huang, Jing Yuan, Liangchao Li and Yali Wang
Many studies indicated that ionospheric total electron content (TEC) prediction is vital for terrestrial and space-based radio-communication systems. In previous TEC prediction schemes based on RNN, they learn TEC representations from previous time steps...
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Mahmoud Ragab, Hesham A. Abdushkour, Louai Maghrabi, Dheyaaldin Alsalman, Ayman G. Fayoumi and Abdullah AL-Malaise AL-Ghamdi
Traffic flow monitoring plays a crucial role in Intelligent Transportation Systems (ITS) by dealing with real-time data on traffic situations and allowing effectual traffic management and optimization. A typical approach used for traffic flow monitoring ...
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Wen-Bin Liu, Phuong Nguyen Thanh, Ming-Yuan Cho and Thao Nguyen Da
The leakage currents are appropriate for determining the contamination level of insulators in the power distribution system, which are efficiently cleaned or replaced during the maintenance schedule. In this research, the hybrid convolution neural networ...
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Zhuoqun Zou, Jing Wang, Ning E, Can Zhang, Zhaocai Wang and Enyu Jiang
Accurate short-term power load forecasting is crucial to maintaining a balance between energy supply and demand, thus minimizing operational costs. However, the intrinsic uncertainty and non-linearity of load data substantially impact the accuracy of for...
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Sakib Shahriar, Noora Al Roken and Imran Zualkernan
The automatic classification of poems into various categories, such as by author or era, is an interesting problem. However, most current work categorizing Arabic poems into eras or emotions has utilized traditional feature engineering and machine learni...
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Jawaher Alghamdi, Yuqing Lin and Suhuai Luo
The prevalence of fake news on social media has led to major sociopolitical issues. Thus, the need for automated fake news detection is more important than ever. In this work, we investigated the interplay between news content and users? posting behavior...
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Yulong Bai, Guolian Li, Tianxiu Lu, Yadong Wu, Weihan Zhang and Yidan Feng
Most existing road network matching algorithms are designed based on previous rules and do not fully utilize the potential of big data and historical tracks. To solve this problem, we introduce a new road network matching algorithm based on deep learning...
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Zhengyi Bao, Jiahao Jiang, Chunxiang Zhu and Mingyu Gao
Accurate estimation of lithium-ion battery state-of-health (SOH) is important for the safe operation of electric vehicles; however, in practical applications, the accuracy of SOH estimation is affected by uncertainty factors, including human operation, w...
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Shun-Chieh Hsieh
The need for accurate tourism demand forecasting is widely recognized. The unreliability of traditional methods makes tourism demand forecasting still challenging. Using deep learning approaches, this study aims to adapt Long Short-Term Memory (LSTM), Bi...
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Abdo Abdullah Ahmed Gassar
Promoting flexible energy demand through response programs in residential neighborhoods would play a vital role in addressing the issues associated with increasing the share of distributed solar systems and balancing supply and demand in energy networks....
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