模糊类概述
模糊类用于根据指定的函数将输入值的变换或重新映射定义为新值。变换过程称为模糊化并且在此过程中会为每个输入值建立模糊分类。变换值的范围从 0 到 1，用于定义分类在指定类或集合中的概率，其中 1 表示恰好在某集合中。每个模糊类都定义一个连续函数，每个函数会捕获不同的变换类型，以达到预期效果。例如，对于与指定值越近成为集合成员的可能性越大的情况，某个函数可能更合适，而对于值越大成为集合成员的可能性越大的情况，另一个函数可能更合适。
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Defines a fuzzy membership function through a Gaussian or normal distribution based around a user-specified midpoint (which is assigned a membership of 1) with a defined spread decreasing to zero. |
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Defines a fuzzy membership function where the larger input values have membership closer to 1. The function is defined by a user-specified midpoint (which is assigned a membership of 0.5) with a defined spread. |
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Defines a fuzzy membership function through a linear transformation between the user-specified minimum value, a membership of 0, to the user-defined maximum value, which is assigned a membership of 1. |
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Defines a fuzzy membership through a function based on the mean and standard deviation, with the larger values having a membership closer to 1. |
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Defines a fuzzy membership through a function based on the mean and standard deviation, with the smaller values having a membership closer to 1. |
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Defines a fuzzy membership function around a specific value which is defined by a user-defined midpoint (which is assigned a membership of 1), with a defined spread decreasing to zero. |
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Defines a fuzzy membership function with the smaller input values having membership closer to 1. The function is defined by a user-specified midpoint (which is assigned a membership of 0.5) with a defined spread. |
使用模糊对象的工具
在多个输入栅格经过变换后，可使用下列工具建立并分析经不同变换的栅格之间的关系：