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1. 发明授权

US06381591B1 Method for transformation of fuzzy logic, which is used to simulate a technical process, into a neural network 失效
标题翻译：将用于模拟技术过程的模糊逻辑转换为神经网络的方法
公开(公告)号：US06381591B1
公开(公告)日：2002-04-30
申请号：US09365779
申请日：1999-08-03
申请人： Wolfgang Hoffmann , Erik Schwulera
发明人： Wolfgang Hoffmann , Erik Schwulera
IPC分类号： G06F1518
CPC分类号： G06N3/0436 , Y10S706/90
摘要： A method for transformation of fuzzy logic (FS) into a neural network (NN), in which, in order to form a defuzzified output value (y2) from normalized single-element functions (F1 . . . Fm), the single-element functions (F1 . . . Fm) are each assigned a singleton position (A1 . . . Am) and at least one singleton weighting factor (R1 . . . Rn), those singleton weighting factors (R1 . . . Rn) which are assigned to the same single-element function (F1 . . . Fm) are additively linked, and the singleton weighting factors (R1 . . . Rn) and the additively linked singleton weighting factors (R1 . . . Rn) are weighted via the corresponding singleton positions (A1 . . . Am) and are additively linked in order to form the defuzzified output value (y2). One advantage of the method according to the invention is that the singleton positions (A1 . . . Am) in the neural network (NN) can be varied, in order to optimize this network, such that their number before and after the optimization process remains constant and thus, in any case, subsequent reverse transformation of the neural network (NN) can be carried out to optimize fuzzy logic (FS). This advantageously allows the use of, in particular, standardized fuzzy system software to describe the optimized fuzzy logic (FS).
摘要翻译：将模糊逻辑（FS）转换为神经网络（NN）的方法，其中为了从归一化单元素函数（F1 ... Fm）形成去模糊化输出值（y2），单元素函数（F1 ... Fm）分别被赋予单例位置（A1 ... Am）和至少一个单例加权因子（R1 ... Rn），分配给那些单例加权因子（R1 ... Rn）对于相同的单元素函数（F1 ... Fm）被加法地链接，并且单重加权因子（R1 ... Rn）和加法相关的单例加权因子（R1 ... Rn）通过相应的单例加权位置（A1 ... Am），并且被加法地链接以形成去模糊化输出值（y2）。根据本发明的方法的一个优点是可以改变神经网络（NN）中的单例位置（A1.A.A），以便优化该网络，使得其优化过程之前和之后的数目保持因此，无论如何，可以执行神经网络（NN）的后续反向转换以优化模糊逻辑（FS）。这有利地允许使用特别是标准化的模糊系统软件来描述优化的模糊逻辑（FS）。

2. 发明授权

US06456990B1 Method for transforming a fuzzy logic used to simulate a technical process into a neural network 失效
标题翻译：将用于模拟技术过程的模糊逻辑转换为神经网络的方法
公开(公告)号：US06456990B1
公开(公告)日：2002-09-24
申请号：US09355710
申请日：1999-11-22
申请人： Wolfgang Hoffmann , Erik Schwulera
发明人： Wolfgang Hoffmann , Erik Schwulera
IPC分类号： G06F1518
CPC分类号： G06N3/0436
摘要： A method for transforming a fuzzy logic system into a neural network, where, in order to simulate membership functions, sigmoid functions are linked together in such a way that, even after the optimization of the neural network, back-transformation of the neural network into a, fuzzy logic system is possible. The advantage of the method described is that a fuzzy logic system can be transformed, in particular component by component, into a neural network and the latter can then be optimized as a whole, i.e. all the components together. The possibility of back-transforming the trained neural network ultimately means that an optimized fuzzy logic system can be obtained. This advantageously makes it possible to use, in particular, standardized fuzzy system software for describing the optimized fuzzy logic system.
摘要翻译：一种将模糊逻辑系统变换为神经网络的方法，其中为了模拟隶属函数，S形函数以这样的方式链接在一起，即即使在神经网络优化之后，将神经网络反向转换成一个模糊逻辑系统是可能的。所描述的方法的优点在于，可以将模糊逻辑系统，特别是按组件分组转换成神经网络，然后将模糊逻辑系统作为整体进行优化，即所有组件在一起。对训练有素的神经网络进行反向转换的可能性最终意味着可以获得优化的模糊逻辑系统。这有利地使得可以特别地使用用于描述优化的模糊逻辑系统的标准化模糊系统软件。

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