APPLICATION OF FUZZY-SETS TO CLIMATIC CLASSIFICATION
APPLICATION OF FUZZY-SETS TO CLIMATIC CLASSIFICATION
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DOI：
10.1016/0168-1923(85)90082-6
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发表时间：
1985-01-01
影响因子：
6.2
通讯作者：
MOORE, AW
中科院分区：
文献类型：
--
作者：
MCBRATNEY, AB;MOORE, AW
模糊集理论作为一种可能的方式来处理气候数据的连续性进行了讨论。本文详细介绍了模糊均值方法，并利用它对澳大利亚和中国的两组气候资料进行了模糊聚类。由此产生的组似乎直观合理，显示了数据的内在连续性和合理的地理邻近性。同时解决的问题是c（组的数量）和m（模糊度）仍然没有解决。一些作者用模糊度的度量来估计givenm，这引起了启发式的争论，而忽略了“什么是群体？"的问题。一些作者认为，隶属函数的大幅跳跃表明数据中自然分组的水平。一个实验性的尝试，以获得一些协议之间的标准措施的futility和这种方法，这同意在一个简单的例子中的直觉预期，导致了一个粗略的，但有前途的方法来解决这个问题，模糊集的方法是现实的和灵活的，并可能提供一个更好的方法来传递信息比分类的气候到离散集。最初的问题接受的概念正式模糊分类和模糊类的感知，一旦建立，似乎从作者的经验是短暂的。
The theory of fuzzy sets is discussed as a possible way of dealing with the continuity of climatic data. The method of fuzzyc-means is described in detail and used to create fuzzy groups for two sets of climatic data, one from Australia and the other from China. The resulting groups seem intuitively reasonable, showing the inherent continuity of the data and a reasonable geographical contiguity.The problem of choosingc(the number of groups) andm(the degree of fuzziness) simultaneously remains unsolved. Measures of fuzziness, which have been used by some authors to estimatecgivenm, give rise to heuristic arguments which ignore the question of “what is a group?”. Some authors have assumed that large jumps in membership functions indicate levels at which natural groupings occur in data. An attempt experimentally to gain some agreement between standard measures of fuzziness and this approach, which agrees with that expected by intuition in a simple example, has led to a cursory yet promising approach to this problem.The fuzzy sets approach is realistic and flexible, and may offer a better approach to information transfer than does the classification of climate into discrete sets. The initial problems of accepting the notion of formal fuzzy classification and of perception of fuzzy classes, once established, appear from the authors' experience to be transient.