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Characteristics and Development Significance of Baishuiyan Tourism Geological Resources in Lianhua County, Jiangxi Province
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作者 Miaolin WANG Long CHEN 《Meteorological and Environmental Research》 CAS 2020年第4期103-109,114,共8页
A systematic survey of tourism geological resources in Baishuiyan tufa platform in Lianhua County,Jiangxi Province was conducted,and the characteristics of its tourism geological resources are summarized.Through the a... A systematic survey of tourism geological resources in Baishuiyan tufa platform in Lianhua County,Jiangxi Province was conducted,and the characteristics of its tourism geological resources are summarized.Through the analysis and comparison of the same type of landscape resources at home and abroad,the development significance of tourism geological resources here is explored,and four points of thinking are proposed. 展开更多
关键词 geological relics Tourism geological resources Ecological civilization construction Baishuiyan
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Low Resource Chinese Geological Text Named Entity Recognition Based on Prompt Learning
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作者 Hang He Chao Ma +6 位作者 Shan Ye Wenqiang Tang Yuxuan Zhou Zhen Yu Jiaxin Yi Li Hou Mingcai Hou 《Journal of Earth Science》 SCIE CAS CSCD 2024年第3期1035-1043,共9页
Geological reports are a significant accomplishment for geologists involved in geological investigations and scientific research as they contain rich data and textual information.With the rapid development of science ... Geological reports are a significant accomplishment for geologists involved in geological investigations and scientific research as they contain rich data and textual information.With the rapid development of science and technology,a large number of textual reports have accumulated in the field of geology.However,many non-hot topics and non-English speaking regions are neglected in mainstream geoscience databases for geological information mining,making it more challenging for some researchers to extract necessary information from these texts.Natural Language Processing(NLP)has obvious advantages in processing large amounts of textual data.The objective of this paper is to identify geological named entities from Chinese geological texts using NLP techniques.We propose the RoBERTa-Prompt-Tuning-NER method,which leverages the concept of Prompt Learning and requires only a small amount of annotated data to train superior models for recognizing geological named entities in low-resource dataset configurations.The RoBERTa layer captures context-based information and longer-distance dependencies through dynamic word vectors.Finally,we conducted experiments on the constructed Geological Named Entity Recognition(GNER)dataset.Our experimental results show that the proposed model achieves the highest F1 score of 80.64%among the four baseline algorithms,demonstrating the reliability and robustness of using the model for Named Entity Recognition of geological texts. 展开更多
关键词 Prompt Learning Named Entity Recognition(NER) low resource geological text text information mining big data geology.
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Have a correct understanding of the attribute of geologic environmentgive full play to the role of geoscience in environmental protection
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作者 Ha Chengyou(Institute of Environmental Geology, Ministry of Geology and Mineral Resources, Beijing 100081 , China) 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 1995年第4期491-501,共11页
Haveacorrectunderstandingoftheattributeofgeologicenvironmentgivefullplaytotheroleofgeoscienceinenvironmental... HaveacorrectunderstandingoftheattributeofgeologicenvironmentgivefullplaytotheroleofgeoscienceinenvironmentalprotectionHaCheng... 展开更多
关键词 geologic environment ATTRIBUTE geologic resources geologic capacity geologic disaster.
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