The complexity of natural conditions leads to the complexity of vegetation types of Taiwan of China, which has both tropical and cold-temperate vegetation types, and could be depicted as the vegetation miniature of Ch...The complexity of natural conditions leads to the complexity of vegetation types of Taiwan of China, which has both tropical and cold-temperate vegetation types, and could be depicted as the vegetation miniature of China or even for the world. The physiognomic-floristic principle was adopted for the vegetation classification of Taiwan. The units of rank from top to bottom are: class of vegetation-type, order of vegetation-type, vegetation-type, alliance group, alliance and association. The high-rank units (class, order and vegetation-type) are classified by ecological physiognomy, while the median and lower units by the species composition of community. At the same time the role of dominant species and character species will also be considered. The dominant species are the major factor concerned with the median ranks (alliance group, and alliance) because they are the chief components of community, additionally their remarkable appearance is easy to identify; the character species (or diagnostic species) are for relatively low ranks (association) because they will clearly show the interspecies relation-ship and the characteristics of community. According to this principle, vegetation of Taiwan is classi-fied into five classes of vegetation-types (forests, thickets, herbaceous vegetation, rock fields vegetation, swamps and aquatic vegetation), 29 orders of vegetation-types (cold-temperate needle-leaved forests, cool-temperate needle-leaved forests, warm-temperate needle-leaved forests, warm needle-leaved forests, deciduous broad-leaved forests, mixed evergreen and deciduous broad-leaved forests, evergreen mossy forests, evergreen sclerophyllous forests, evergreen broad-leaved forests, tropical rain forests, tropical monsoon forests, coastal forests, warm bamboo forests, evergreen needle-leaved thickets, sclerophyllous thickets, deciduous broad-leaved thickets, evergreen broad-leaved thickets, xerothermic thorn-succulent thickets, bamboo thickets, meadows, sparse shrub grasslands, savannahic grasslands, sparse scree communities, chasmophytic vegetation, woody swamps, herbaceous swamps, moss bogs, fresh water aquatic vegetation, salt water aquatic vegetation) and 53 vegetation-types. The main alliances of each vegetation-type are described.展开更多
According to the positive correlation of coal ash content and natural gamma, using a new coal core reposition method, which is ordered by global and local extreme, coal samples from medium-thickness seam are reasonabl...According to the positive correlation of coal ash content and natural gamma, using a new coal core reposition method, which is ordered by global and local extreme, coal samples from medium-thickness seam are reasonably located. Inte- grated the data of coal macrostructure characteristics, coal petrography analysis and coal gas production test, it studies the rela- tionship between coalbody structure and amplitude variation of different well logging data, and the tectonic coal recognition method with well logging data in fresh-water mud invasion. The results show that： the anomalous response of natural gamma ray, neutron, density and apparent resistivity does not reflect the coalbody structure type. In fresh-water drilling mud invasion, using the crossplot technique of dual-lateral, RXO resistivity response and the coalbody structure can classify granulated coal accurately; the proposed method is of good practicability and high reliability.展开更多
In recent decades, the typical E1 Nifio events with the warmest SSTs in the tropical eastern Pacific have become less common, and a different of E1 Nifio with the wannest SSTs in the central the east and west by coole...In recent decades, the typical E1 Nifio events with the warmest SSTs in the tropical eastern Pacific have become less common, and a different of E1 Nifio with the wannest SSTs in the central the east and west by cooler Pacific, which is flanked on SSTs, has become more frequent. The more recent type of E1 Nifio was referred to as central Pacific E1 Nifio, warm pool E1 Nifio, or dateline E1 Nifio, or the E1 Nifio Modoki. Central Pacific E1 Nifio links to a different tropical-to-extratropical teleconnection and exerts different impacts on climate, and several clas- sification approaches have been proposed. In this study, a new classification approach is proposed, which is based on the linear combination （sum or difference） of the two leading Empirical Orthogonal Functions （EOFs） of tropi- cal Pacific Ocean sea surface temperature anomaly （SSTA）, and the typical E1 Nifio index （TENI） and the central E1 Nifio index （CENI） are able to be derived by projecting the observed SSTA onto these combinations. This classification not only reflects the characteristics of non-orthogonality between the two types of events but also yields one period peaking at approximate two to seven years. In particular, this classification can distin- guish the different impacts of the two types of events on rainfall in the following summer in East China. The typi- cal E1 Nifio events tend to induce intensified rainfall in the Yangtze River valley, whereas the central Pacific El Nifio tends to induce intensified rainfall in the Huaihe River valley. Thus, the present approach may be appropriate for studying the impact of different types of E1 Nifio on the East Asian climate.展开更多
The traditional market segmentation was based on ＂transcendental rationality＂ or ＂Situational Rationality＂, studies shows that it had disadvantages. This paper states the ＂Situational＂ integrated rationality hyp...The traditional market segmentation was based on ＂transcendental rationality＂ or ＂Situational Rationality＂, studies shows that it had disadvantages. This paper states the ＂Situational＂ integrated rationality hypothesis and then comes up with the market segmenting models and classification algorithm basing on this hypothesis. This algorithm combined the Rough Set theory and Neural Networks in application, which overcome the dilemma that caused complicated network structure and long training time by only using Neural Networks and influenced the classification precision caused by noise disturbance by only using Rough Set methods. Finally, the paper did a comparison experiment between the traditional method and the method we came up, the results shows that the model and algorithm has its advantage on every aspects.展开更多
文摘The complexity of natural conditions leads to the complexity of vegetation types of Taiwan of China, which has both tropical and cold-temperate vegetation types, and could be depicted as the vegetation miniature of China or even for the world. The physiognomic-floristic principle was adopted for the vegetation classification of Taiwan. The units of rank from top to bottom are: class of vegetation-type, order of vegetation-type, vegetation-type, alliance group, alliance and association. The high-rank units (class, order and vegetation-type) are classified by ecological physiognomy, while the median and lower units by the species composition of community. At the same time the role of dominant species and character species will also be considered. The dominant species are the major factor concerned with the median ranks (alliance group, and alliance) because they are the chief components of community, additionally their remarkable appearance is easy to identify; the character species (or diagnostic species) are for relatively low ranks (association) because they will clearly show the interspecies relation-ship and the characteristics of community. According to this principle, vegetation of Taiwan is classi-fied into five classes of vegetation-types (forests, thickets, herbaceous vegetation, rock fields vegetation, swamps and aquatic vegetation), 29 orders of vegetation-types (cold-temperate needle-leaved forests, cool-temperate needle-leaved forests, warm-temperate needle-leaved forests, warm needle-leaved forests, deciduous broad-leaved forests, mixed evergreen and deciduous broad-leaved forests, evergreen mossy forests, evergreen sclerophyllous forests, evergreen broad-leaved forests, tropical rain forests, tropical monsoon forests, coastal forests, warm bamboo forests, evergreen needle-leaved thickets, sclerophyllous thickets, deciduous broad-leaved thickets, evergreen broad-leaved thickets, xerothermic thorn-succulent thickets, bamboo thickets, meadows, sparse shrub grasslands, savannahic grasslands, sparse scree communities, chasmophytic vegetation, woody swamps, herbaceous swamps, moss bogs, fresh water aquatic vegetation, salt water aquatic vegetation) and 53 vegetation-types. The main alliances of each vegetation-type are described.
文摘According to the positive correlation of coal ash content and natural gamma, using a new coal core reposition method, which is ordered by global and local extreme, coal samples from medium-thickness seam are reasonably located. Inte- grated the data of coal macrostructure characteristics, coal petrography analysis and coal gas production test, it studies the rela- tionship between coalbody structure and amplitude variation of different well logging data, and the tectonic coal recognition method with well logging data in fresh-water mud invasion. The results show that： the anomalous response of natural gamma ray, neutron, density and apparent resistivity does not reflect the coalbody structure type. In fresh-water drilling mud invasion, using the crossplot technique of dual-lateral, RXO resistivity response and the coalbody structure can classify granulated coal accurately; the proposed method is of good practicability and high reliability.
基金supported by the Nationa Basic Research Program of China, "Oceanic circulation, structure characteristics, variation mechanisms, and climate effects of thewarm pool in the tropical Pacific", under Grant 2012CB417403
文摘In recent decades, the typical E1 Nifio events with the warmest SSTs in the tropical eastern Pacific have become less common, and a different of E1 Nifio with the wannest SSTs in the central the east and west by cooler Pacific, which is flanked on SSTs, has become more frequent. The more recent type of E1 Nifio was referred to as central Pacific E1 Nifio, warm pool E1 Nifio, or dateline E1 Nifio, or the E1 Nifio Modoki. Central Pacific E1 Nifio links to a different tropical-to-extratropical teleconnection and exerts different impacts on climate, and several clas- sification approaches have been proposed. In this study, a new classification approach is proposed, which is based on the linear combination （sum or difference） of the two leading Empirical Orthogonal Functions （EOFs） of tropi- cal Pacific Ocean sea surface temperature anomaly （SSTA）, and the typical E1 Nifio index （TENI） and the central E1 Nifio index （CENI） are able to be derived by projecting the observed SSTA onto these combinations. This classification not only reflects the characteristics of non-orthogonality between the two types of events but also yields one period peaking at approximate two to seven years. In particular, this classification can distin- guish the different impacts of the two types of events on rainfall in the following summer in East China. The typi- cal E1 Nifio events tend to induce intensified rainfall in the Yangtze River valley, whereas the central Pacific El Nifio tends to induce intensified rainfall in the Huaihe River valley. Thus, the present approach may be appropriate for studying the impact of different types of E1 Nifio on the East Asian climate.
基金This paper is financial aided by the National Natural Science Foundation project in China （No. 70640008）, The National Social Science Foundation project in China （No. 05BJY043） and The Foundation Project of Inner Mongolia education office （No. N J02019）.
文摘The traditional market segmentation was based on ＂transcendental rationality＂ or ＂Situational Rationality＂, studies shows that it had disadvantages. This paper states the ＂Situational＂ integrated rationality hypothesis and then comes up with the market segmenting models and classification algorithm basing on this hypothesis. This algorithm combined the Rough Set theory and Neural Networks in application, which overcome the dilemma that caused complicated network structure and long training time by only using Neural Networks and influenced the classification precision caused by noise disturbance by only using Rough Set methods. Finally, the paper did a comparison experiment between the traditional method and the method we came up, the results shows that the model and algorithm has its advantage on every aspects.
