Showing 141 - 160 results of 245 for search '"Yunnan Province"', query time: 0.05s Refine Results
  1. 141
  2. 142

    Study on the Annual Variation Characteristics of Runoff in Yunnan by GU Guihua, LI Xuehui, YU Shoulong, DUAN Lusong

    Published 2021-01-01
    “…To study the annual variation characteristics of runoff in Yunnan Province and analyze the main influencing factors,based on the observed monthly and annual rainfall and runoff data of 9 representative hydrological stations in 6 major river basins in Yunnan from 1956 to 2016,this paper analyzes the annual runoff distribution in terms of the uniformity,concentration and relative variation range.The research shows that:①The uniformity coefficient (C<sub>u</sub>) of runoff distribution in many years ranges from 0.55 to 1.21,and the concentration (C<sub>n</sub>) ranges from 0.23 to 0.66,so the runoff is unevenly distributed in the whole province.②The C<sub>u</sub> and C<sub>n</sub> decrease in general.Especially after 2000,the annual distribution of runoff shows a trend of uniformity.③The runoff concentration is relatively high in the Yangtze River Basin and the Honghe River Basin,and the annual runoff distribution is flat in the Lancang River Basin and the Zhujiang River Basin.④The uniformity trend of annual runoff distribution is closely related to human activities in the basin.…”
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  3. 143

    A new species of Cyrtodactylus Gray, 1827 (Squamata, Gekkonidae) from Yunnan Nangunhe National Nature Reserve, China by Shuo Liu, Zhimin Li, Wenguang Duan, Mian Hou, Dingqi Rao

    Published 2025-01-01
    “…A new forest-dwelling species of the Cyrtodactylus chauquangensis group is described from southwestern Yunnan Province, China. Phylogenetically, it was recovered as the sister species of C. zhenkangensis, with a genetic distance of 9.2% in the ND2 gene. …”
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  4. 144

    Seismic Response Analysis of Jointed Rock Slope under Pulse-Like Ground Motions by Xijun Jia, Yu Zhang, Ziyi Zhang

    Published 2024-01-01
    “…To reveal the progressive failure mechanism of jointed rock slope under pulse-like ground motions, a 3D discrete element numerical model of jointed rock slope in the northern Yunnan province was established to analyze the acceleration, dynamic displacement, and failure modes under bidirectional pulse-like ground motions. …”
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  5. 145
  6. 146

    Application Review of Comprehensive Multi-index Evaluation Methods in River Health Evaluation by YANG Xiaoyan, WANG Chi, WU Tian, XIA Tiyuan

    Published 2024-01-01
    “…To understand the current research progress and direction of comprehensive multi-index evaluation methods,and supplement the principle and method of evaluation index screening,this paper summarizes the research progress of the comprehensive multi-index evaluation method in river health evaluation at home and abroad.Firstly,the concept and evaluation principle of comprehensive multi-index evaluation are summarized from the perspective of river health evaluation objects and evaluation methods by tracing the domestic and foreign literature.Meanwhile,the three hierarchies of river health evaluation are illustrated by taking the target-criterion-index structure of river health evaluation in Yunnan Province as an example.Secondly,the current research progress of comprehensive multi-index evaluation methods and the index selection rationality are emphasized.Finally,the problems existing in the comprehensive multi-index evaluation methods are analyzed and the corresponding solutions are put forward.As a result,this paper provides references for river health management in China,and also scientific and technological support for the smooth promotion of river chief systems in various places.…”
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  7. 147

    Species-Specific Gene, spt5, in the Qualitative and Quantitative Detection of Boletus reticulatus by Zhan Lei, Chen Zhang, Yinjiao Li, Lunzhao Yi, Ying Shang

    Published 2022-01-01
    “…Boletus reticulatus is a wild edible fungus with high nutritional value in Yunnan Province. In this study, B. reticulatus was used as the research object to diagnose the species characteristics. …”
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  8. 148

    Efficacy of contralateral acupuncture in women with migraine without aura: protocol for a randomised controlled trial by Ling Zhao, Qifu Li, Yanan Wang, Jialei Feng, Xinghe Zhang, Siwen Zhao, Chonghui Xing, Yongli Song, Xuanxiang Zeng, Meng Kong, Yunqiu Zheng, Taipin Guo

    Published 2022-06-01
    “…Adverse events will be collected and recorded during each treatment.Ethics and dissemination Ethics approval was obtained from the Ethics Committee of the Sports Trauma Specialist Hospital of Yunnan Province (2021-01). All participants will provide written informed consent before randomisation. …”
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  9. 149

    1600 AD Huaynaputina Eruption (Peru), Abrupt Cooling, and Epidemics in China and Korea by Jie Fei, David D. Zhang, Harry F. Lee

    Published 2016-01-01
    “…In addition, there was unseasonable snowfall that autumn within Yunnan Province. Widespread disease outbreaks occurred in August, September, and October in northern and southern China. …”
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  10. 150

    Investigation and Identification of Fungal Diseases of <i>Aloe barbadensis</i> in China by Guohui Zhang, Qingjia Wan, Xiangyang Li, Jie Deng

    Published 2025-01-01
    “…The <i>Aloe barbadensis</i> industry plays an important role in the economic development of Yuanjiang county of Yuxi city in Yunnan province, China. In order to reduce the harm of diseases and ensure the quality of products, the occurrence of <i>A. barbadensis</i> was investigated. …”
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  11. 151

    Research on Annual Runoff Prediction Based on EMD-LSTM-ANFIS Model by HU Shunqiang, CUI Dongwen

    Published 2021-01-01
    “…To improve the accuracy of runoff prediction,this paper proposes a runoff prediction model based on the combination of empirical mode decomposition (EMD),long short-term memory (LSTM) neural network,and adaptive neuro-fuzzy inference system (ANFIS),decomposes the original runoff sequence into multiple regular component sequences through EMD,and reconstructs the phase space of each component sequence by the autocorrelation function method (AFM) and the false nearest neighbor method (FNN) to determine the input and output vectors,establishes the EMD-LSTM-ANFIS prediction model,and constructs the EMD-LSTM,EMD-ANFIS,LSTM,ANFIS as comparison models,as well as predicts and compares the annual runoff of the Longtan Station in Yunnan Province by the five models.The results show that the average relative error of the EMD-LSTM-ANFIS model for the annual runoff prediction is 3.18%,which is reduced by 55.0%、65.2%、68.1%、78.4% compared with the EMD-LSTM,EMD-ANFIS,LSTM,and ANFIS models respectively,with higher prediction accuracy and stronger generalization ability.Therefore,the EMD-LSTM-ANFIS model is feasible and reliable for runoff prediction.…”
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  12. 152

    On new spider species of the genus Episinus (Araneae, Theridiidae) from China and proposal of five species groups by Yun Liang, Jinnan Liu, Haiqiang Yin, Xiang Xu

    Published 2025-02-01
    “…. (♀) from Jiangxi Province, E. implicatus sp. nov. (♀) from Yunnan Province and E. pseudonubilus sp. nov. (♂♀) from Shaanxi Province. …”
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  13. 153

    Research on Monthly Runoff Forecast in Dry Seasons Based on GEO-RVM Model by ZHANG Yajie, CUI Dongwen

    Published 2022-01-01
    “…To improve the accuracy of monthly runoff forecasts during dry seasons,this study proposes a forecasting method that combines the golden eagle optimization (GEO) algorithm and the relevance vector machine (RVM).On the basis of the runoff data of 67 a from a hydrological station in Yunnan Province,the monthly runoff with good correlation before the forecast month is selected as the influencing factor of forecasts,and the influencing factor is reduced in dimension by principal component analysis (PCA).The kernel width factor and hyperparameters of RVM are optimized by the GEO algorithm,and the GEO-RVM model is built to forecast the monthly runoff of the station during the dry season from November to April of the following year.Moreover,the forecast results are compared with those of the GEO-based support vector machine (SVM) model (GEO-SVM).The results demonstrate that the average relative errors of the GEO-RVM model for the monthly runoff forecasts from November to April of the following year are 8.59%,7.34%,5.97%,6.07%,5.99%,and 5.04%,respectively,which means the accuracy is better than that of the GEO-SVM model.The GEO algorithm can effectively optimize the kernel width factor and hyperparameters of RVM,and the GEO-RVM model has better forecast accuracy,which can be used for monthly runoff forecasting during dry seasons.…”
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  14. 154

    Applicability Analysis of Machine Learning Model in Hydrological Forecasting in Karst Areas by ZHAO Zejin, SUN Wei, ZHOU Bin, ZHANG Xuan, WANG Gaoxu, WU Wei, LI Wenjie, YAO Ye

    Published 2024-01-01
    “…For hydrological forecasting in karst areas,existing research mainly uses hydrological models based on physical mechanisms,while rare research focuses on machine learning models.To explore the applicability of machine learning models in karst areas, this paper utilizes the LSTM model and random forest model to simulate the daily runoff and field floods at Tangdian hydrological station,using the Shadian River basin in Yunnan Province as the study area.The modified Xin'anjiang model for karst areas is taken as a reference.The results show that both the machine learning model and the modified Xin'anjiang model have achieved good results in simulating the daily runoff process, with the LSTM model showing better simulation results.In the simulation of floods,the modified Xin'anjiang model achieves Class A forecast accuracy.The machine learning models have better forecast results for the 6-hour forecasting period than the modified Xin'anjiang model,while the forecast results for the 24-hour forecasting period do not meet the accuracy requirements of the forecast operation.The study provides a reference for hydrological forecasting in karst areas by studying the characteristics and forecasting accuracy of two machine learning models and a hydrologic model.…”
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  15. 155

    Investigating the factors that influence Chinese undergraduate students' sustained use of open source communities. by Xinyi Wang, Rafiza Abdul Razak, Siti Hajar Halili

    Published 2024-01-01
    “…The study used random stratified sampling to survey 803 undergraduate students in Yunnan Province. The influencing factors in innovation diffusion theory and the technology acceptance model were analyzed using the partial least squares structural equation model. …”
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  16. 156
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  18. 158

    Study on the Impact of Step Layout on Secondary Energy Dissipation and Flow Pattern of Spillway Tailwater by YANG Ruiguo, QIU Yong, CHEN Yubin, YUE Cuiyun, YIN Xingtang

    Published 2021-01-01
    “…A secondary energy dissipation is required between the sill underflow stilling basin and the downstream tailrace at the outlet of the Dabaitian Reservoir spillway in Fengqing County,Yunnan Province.At the same time,the stepped energy dissipation section is connected through a 40° bend to adapt to the change of terrain.Through the hydraulic model test research,based on the original plan,after the water flowing out of the stilling basin passes through the stepped bend,an obvious Z-shaped folded water flow is produced on the plane.When it occurs once in 30 years,the water velocity on the left side of the bend reaches 9.97 m/s,threatening the stability of the rock formations along the slope of the left bank.The modified plan of step backward movement can effectively improve the flow pattern in the bend.On this basis,an improved plan to reduce the size of the original step (2.50 m×1.50 m to 1.00 m×0.60 m) is proposed to avoid falling water flow at the location of the step in the case of frequent small-flow floods.The research results show that in the improved stepped energy dissipation combination for bend,the water depth distribution along the cross section of the tailrace downstream of the stilling basin is relatively even in the case of small-flow floods,and the flow patten is improved significantly,so the water flowing back to the river smoothly is realized under frequent flood discharges.…”
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  19. 159

    Stability analysis of an expansive soil slope under heavy rainfall conditions with different anchor reinforcements by Yuqi Liu

    Published 2025-01-01
    “…Focusing on a project in Yunnan Province, numerical simulation software is employed to address slope stability challenges. …”
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  20. 160

    Research on Runoff Prediction Based on EMD-FBI-ELM Model by ZHANG Yajie, CUI Dongwen

    Published 2022-01-01
    “…,EMD-FBI-SVM,FBI-ELM and FBI-SVM.Finally,the EMD-FBI-ELM,EMD-FBI-SVM,FBI-ELM and FBI-SVM models are verified and analyzed with the annual runoff at the Gulaohe River Hydrological Station in Yunnan Province as a prediction example.The results show that the average relative error of the EMD-FBI-ELM model is 3.97% for the annual runoff prediction,which is 53.9%,81.7% and 86.5% lower than those of the EMD-FBI-SVM,FBI-ELM and FBI-SVM models,respectively.The EMD-FBI-ELM model is feasible for runoff prediction,and the model and optimization method can provide reference for relevant prediction research.…”
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