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  Indian J Med Microbiol
 

Figure 1: The TSK ANFIS architecture. Layer 1: Each node represents a linguistic label. Here, The Gaussian membership functions of each fuzzy set according to Eq. 4, Layer 2: Every node is a fixed node whose output is the product of all the incoming signals from Layer 1, Layer 3: Every node is a fixed node labeled with “N,” Layer 4: Every node L in this layer is a node function yLw̄L where w̄L is the output of Layer 3, Layer 5: The single node in this layer is a fixed node. It computes the overall output as the summation of all incoming signals

Figure 1: The TSK ANFIS architecture. Layer 1: Each node represents a linguistic label. Here, The Gaussian membership functions of each fuzzy set according to Eq. 4, Layer 2: Every node is a fixed node whose output is the product of all the incoming signals from Layer 1, Layer 3: Every node is a fixed node labeled with “N,” Layer 4: Every node L in this layer is a node function <i>y</i><sup>L</sup><i>w</i>̄<sup>L</sup> where <i>w</i>̄<sup>L</sup> is the output of Layer 3, Layer 5: The single node in this layer is a fixed node. It computes the overall output as the summation of all incoming signals