The concept of the degree of similarity between interval-valued intuitionistic fuzzy sets （IVIFSs） is introduced, and some distance measures between IVIFSs are defined based on the Hamming distance, the normalized H...The concept of the degree of similarity between interval-valued intuitionistic fuzzy sets （IVIFSs） is introduced, and some distance measures between IVIFSs are defined based on the Hamming distance, the normalized Hamming distance, the weighted Hamming distance, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance, etc. Then, by combining the Hausdorff metric with the Hamming distance, the Euclidean distance and their weighted versions, two other similarity measures between IVIFSs, i. e., the weighted Hamming distance based on the Hausdorff metric and the weighted Euclidean distance based on the Hausdorff metric, are defined, and then some of their properties are studied. Finally, based on these distance measures, some similarity measures between IVIFSs are defined, and the similarity measures are applied to pattern recognitions with interval-valued intuitionistic fuzzy information.展开更多
Within the context of global change, marine sensitive factors or Marine Essential Climate Variables have been defined by many projects, and their sensitive spatial regions and time phases play significant roles in reg...Within the context of global change, marine sensitive factors or Marine Essential Climate Variables have been defined by many projects, and their sensitive spatial regions and time phases play significant roles in regional sea-air interactions and better understanding of their dynamic process. In this paper, we propose a cluster-based method for marine sensitive region extraction and representation. This method includes a kernel expansion algorithm for extracting marine sensitive regions, and a field-object triple form, integration of object-oriented and field-based model, for representing marine sensitive objects. Firstly, this method recognizes ENSO-related spatial patterns using empirical orthogonal decomposition of long term marine sensitive factors and correlation analysis with multiple ENSO index. The cluster kernel, defined by statistics of spatial patterns, is initialized to carry out spatial expansion and cluster mergence with spatial neighborhoods recursively, then all the related lattices with similar behavior are merged into marine sensitive regions. After this, the Field-object triple form of < O, A, F > is used to represent the marine sensitive objects, both with the discrete object with a precise extend and boundary, and the continuous field with variations dependent on spatial locations. Finally, the marine sensitive objects about sea surface temperature are extracted, represented and analyzed as a case of study, which proves the effectiveness and the efficiency of the proposed method.展开更多
Suffering from fragile environment, poor accessibility and infrastructure, as well as social,political and economic marginality, the interprovincial mountain geographical entities are difficult areas for the regional ...Suffering from fragile environment, poor accessibility and infrastructure, as well as social,political and economic marginality, the interprovincial mountain geographical entities are difficult areas for the regional governance in China.By analyzing the spatial patterns and the influencing factors of the interprovincial mountain geographical names(IMGNs), the goal of this research is to clarify the geographical features of IMGNs and offer alternatives for the management of interprovincial mountain regions in China. The spatial visualization,the analysis of spatial agglomeration and the influencing factors of IMGNs were all implemented under a geographical information system. Results showed that there were 6869 IMGNs in China according to the database of "China's Second National Survey of Geographical Names(2014-2018)",including 4209 mountain geographical names, 1684 mountain peak geographical names and 976 the other mountain geographical names. Hunan Province had the largest number of names while Shanghai had the smallest number of names. In addition, the spatial variance of the mountain peak names and the mountain names were larger than that of the other mountain geographical names, and the IMGNs showed a significant clustering phenomenon in the southern part of China. The relative elevation and the population had an impact on the distribution of the IMGNs. The largest number of the names occurred where the relative elevation was between 1000-2000 m and where the population was between 40-50 million. Density of unnamed interprovincial mountain geographical entities declined from west to east in China. The analysis of generic names of different types of IMGNs implied that the naming of IMGNs is inconsistent. Based on these analyses, it is suggested that the government should take the IMGNs as management units, strengthen the naming of unnamed interprovincial mountain geographical entities, standardize the generic names of IMGNs and identify areas of poverty based on the survey of IMGNs.展开更多
The seasonal variations in biomass, abundance, and species composition of plankton in relation to hydrography were studied in the saline Bange Lake, northern Tibet, China. Sampling was carried out between one to three...The seasonal variations in biomass, abundance, and species composition of plankton in relation to hydrography were studied in the saline Bange Lake, northern Tibet, China. Sampling was carried out between one to three times per month from May 2001 to July 2002. Salinity ranged from 14 to 146. The air and water temperature exhibited a clear seasonal pattern, and mean annual temperatures were approximately 4.8℃ and 7.3℃, respectively. The lowest water temperature occurred in winter from December to March at-2℃ and the highest in June and July at 17.7℃. Forty-one phytoplankton taxa, 21 zooplankton, and 5 benthic or facultative zooplankton were identifi ed. The predominant phytoplankton species were Gloeothece linearis, Oscillatoria tenuis, Gloeocapsa punctata, Ctenocladus circinnatus, Dunaliella salina, and Spirulina major. The predominant zooplankton species included H olophrya actra, Brachionus plicatilis, Daphniopsis tibetana, Cletocamptus dertersi, and A rctodiaptomus salinus. The mean annual total phytoplankton density and biomass for the entire lake were 4.52×10^7 cells/L and 1.60 mg/L, respectively. The annual mean zooplankton abundance was 52, 162, 322, and 57, 144 ind./L, in the three sublakes. The annual mean total zooplankton biomass in Lakes 1–3 was 1.23, 9.98, and 2.13 mg/L, respectively. The annual mean tychoplankton abundances in Bg1, 2, and 3 were 47, 67, and 654 ind./L. The annual mean tychoplankton biomass was 2.36, 0.16, and 2.03 mg/L, respectively. The zooplankton biomass（including tychoplankton） in the lake was 9.11 mg/L. The total number of plankton species in the salt lake was signifi cantly negatively correlated with salinity.展开更多
基金The National Natural Science Foundation of China (No70571087)the National Science Fund for Distinguished Young Scholarsof China (No70625005)
文摘The concept of the degree of similarity between interval-valued intuitionistic fuzzy sets （IVIFSs） is introduced, and some distance measures between IVIFSs are defined based on the Hamming distance, the normalized Hamming distance, the weighted Hamming distance, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance, etc. Then, by combining the Hausdorff metric with the Hamming distance, the Euclidean distance and their weighted versions, two other similarity measures between IVIFSs, i. e., the weighted Hamming distance based on the Hausdorff metric and the weighted Euclidean distance based on the Hausdorff metric, are defined, and then some of their properties are studied. Finally, based on these distance measures, some similarity measures between IVIFSs are defined, and the similarity measures are applied to pattern recognitions with interval-valued intuitionistic fuzzy information.
基金supported by the director projects of Centre for Earth Observation and Digital Earth(CEODE)(Nos.Y2ZZ06101B and Y2ZZ18101B)the State Key Laboratory of Resources and Environmental Information System project+1 种基金the National Natural Science Foundation of China(project No.41371385)the National High Technology Research and Development Program of China(project No.2012AA12A403-5)
文摘Within the context of global change, marine sensitive factors or Marine Essential Climate Variables have been defined by many projects, and their sensitive spatial regions and time phases play significant roles in regional sea-air interactions and better understanding of their dynamic process. In this paper, we propose a cluster-based method for marine sensitive region extraction and representation. This method includes a kernel expansion algorithm for extracting marine sensitive regions, and a field-object triple form, integration of object-oriented and field-based model, for representing marine sensitive objects. Firstly, this method recognizes ENSO-related spatial patterns using empirical orthogonal decomposition of long term marine sensitive factors and correlation analysis with multiple ENSO index. The cluster kernel, defined by statistics of spatial patterns, is initialized to carry out spatial expansion and cluster mergence with spatial neighborhoods recursively, then all the related lattices with similar behavior are merged into marine sensitive regions. After this, the Field-object triple form of < O, A, F > is used to represent the marine sensitive objects, both with the discrete object with a precise extend and boundary, and the continuous field with variations dependent on spatial locations. Finally, the marine sensitive objects about sea surface temperature are extracted, represented and analyzed as a case of study, which proves the effectiveness and the efficiency of the proposed method.
基金supported by the Project of "Atlas of the People's Republic of China (New Century Edition)”funded by Ministry of Science and Technology, China (No. 2013FY112800)
文摘Suffering from fragile environment, poor accessibility and infrastructure, as well as social,political and economic marginality, the interprovincial mountain geographical entities are difficult areas for the regional governance in China.By analyzing the spatial patterns and the influencing factors of the interprovincial mountain geographical names(IMGNs), the goal of this research is to clarify the geographical features of IMGNs and offer alternatives for the management of interprovincial mountain regions in China. The spatial visualization,the analysis of spatial agglomeration and the influencing factors of IMGNs were all implemented under a geographical information system. Results showed that there were 6869 IMGNs in China according to the database of "China's Second National Survey of Geographical Names(2014-2018)",including 4209 mountain geographical names, 1684 mountain peak geographical names and 976 the other mountain geographical names. Hunan Province had the largest number of names while Shanghai had the smallest number of names. In addition, the spatial variance of the mountain peak names and the mountain names were larger than that of the other mountain geographical names, and the IMGNs showed a significant clustering phenomenon in the southern part of China. The relative elevation and the population had an impact on the distribution of the IMGNs. The largest number of the names occurred where the relative elevation was between 1000-2000 m and where the population was between 40-50 million. Density of unnamed interprovincial mountain geographical entities declined from west to east in China. The analysis of generic names of different types of IMGNs implied that the naming of IMGNs is inconsistent. Based on these analyses, it is suggested that the government should take the IMGNs as management units, strengthen the naming of unnamed interprovincial mountain geographical entities, standardize the generic names of IMGNs and identify areas of poverty based on the survey of IMGNs.
基金Supported by the China Geological Survey(Resources No.[2002]004)the National Natural Science Foundation of China(No.30371112)+1 种基金the Liaoning Science and Technology Foundation(Nos.002119,20022100)the Special Program for Key Basic Research of Ministry of Science and Technology,China(No.2014FY210700)
文摘The seasonal variations in biomass, abundance, and species composition of plankton in relation to hydrography were studied in the saline Bange Lake, northern Tibet, China. Sampling was carried out between one to three times per month from May 2001 to July 2002. Salinity ranged from 14 to 146. The air and water temperature exhibited a clear seasonal pattern, and mean annual temperatures were approximately 4.8℃ and 7.3℃, respectively. The lowest water temperature occurred in winter from December to March at-2℃ and the highest in June and July at 17.7℃. Forty-one phytoplankton taxa, 21 zooplankton, and 5 benthic or facultative zooplankton were identifi ed. The predominant phytoplankton species were Gloeothece linearis, Oscillatoria tenuis, Gloeocapsa punctata, Ctenocladus circinnatus, Dunaliella salina, and Spirulina major. The predominant zooplankton species included H olophrya actra, Brachionus plicatilis, Daphniopsis tibetana, Cletocamptus dertersi, and A rctodiaptomus salinus. The mean annual total phytoplankton density and biomass for the entire lake were 4.52×10^7 cells/L and 1.60 mg/L, respectively. The annual mean zooplankton abundance was 52, 162, 322, and 57, 144 ind./L, in the three sublakes. The annual mean total zooplankton biomass in Lakes 1–3 was 1.23, 9.98, and 2.13 mg/L, respectively. The annual mean tychoplankton abundances in Bg1, 2, and 3 were 47, 67, and 654 ind./L. The annual mean tychoplankton biomass was 2.36, 0.16, and 2.03 mg/L, respectively. The zooplankton biomass（including tychoplankton） in the lake was 9.11 mg/L. The total number of plankton species in the salt lake was signifi cantly negatively correlated with salinity.
