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- 545554 (2)
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- ANFIS (1)
- Clustering (1)
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- FCM (1)
- Fuzzy system; FIS; ANFIS; Neural networks; Accuracy of the fuzzy system; Liver disorders (1)
- Fuzzy-Cluster System (1)
- Interval type-2 membership functions (1)
- Interval type-2 non-singleton type-2 FLS (1)
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- Neuro-fuzzy system; Fuzzy classifier; Fuzzy inference for classification; Fuzzy perceptron; Nfclass; Confusion fuzzy matrix; Bayesian classification; ROC technique; Lung cancer diagnosis. (1)
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Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Fuzzy Mathematical Models Of Type-1 And Type-2 For Computing The Parameters And Its Applications, R.W. W. Hndoosh
Fuzzy Mathematical Models Of Type-1 And Type-2 For Computing The Parameters And Its Applications, R.W. W. Hndoosh
R. W. Hndoosh
This work provides mathematical formulas and algorithm in order to calculate the derivatives that being necessary to perform Steepest Descent models to make T1 and T2 FLSs much more accessible to FLS modelers. It provides derivative computations that are applied on different kind of MFs, and some computations which are then clarified for specific MFs. We have learned how to model T1 FLSs when a set of training data is available and provided an application to derive the Steepest Descent models that depend on trigonometric function (SDTFM). This work, also focused on an interval type-2 non-singleton type-2 FLS (IT2 NS-T2 …
Fuzzy Mathematical Models For The Analysis Of Fuzzy Systems With Application To Liver Disorders, R.W. W. Hndoosh
Fuzzy Mathematical Models For The Analysis Of Fuzzy Systems With Application To Liver Disorders, R.W. W. Hndoosh
R. W. Hndoosh
The main objective of this model is to focus on how to use the model of fuzzy system to solve fuzzy mathematics problems. Some mathematical models based on fuzzy set theory, fuzzy systems and neural network techniques seem very well suited for typical technical problems. We have proposed an extension model of a fuzzy system to N-dimension, using Mamdani's minimum implication, the minimum inference system, and the singleton fuzzifier with the center average defuzzifier. Here construct two different models namely a fuzzy inference system and an adaptive fuzzy system using neural network. We have extended the theorem for accuracy of …
Fuzzy Mathematical Model For Detection Of Lung Cancer Using A Multi-Nfclass With Confusion Fuzzy Matrix For Accuracy, R.W. W. Hndoosh
Fuzzy Mathematical Model For Detection Of Lung Cancer Using A Multi-Nfclass With Confusion Fuzzy Matrix For Accuracy, R.W. W. Hndoosh
R. W. Hndoosh
and detection of lung cancer data. This model depends on a generic model of a fuzzy perceptron, which can be used to derive a neural fuzzy system for specific domains. The multi neuron-fuzzy classification (Multi-NFClass) model proposed that uses input, hidden layers, output, and subclasses that have a multitude in each class. This model derives fuzzy rules to classify patterns into a number of crisp classes. Firstly, an attempt is made to describe fuzzy if–then rules, and construction of the fuzzy if–then rule, that are determined by the simple steps when its antecedent fuzzy sets are specified by genetic operations, …
Mathematical Structure Of Fuzzy Modeling Of Medical Diagnoses By Using Clustering Models, R.W. W. Hndoosh
Mathematical Structure Of Fuzzy Modeling Of Medical Diagnoses By Using Clustering Models, R.W. W. Hndoosh
R. W. Hndoosh
An Adaptive-Network-based Fuzzy Inference System ANFIS with different techniques of clustering is successfully developed to solve one of the problems of medical diagnoses, because it has the advantage of powerful modeling ability. In this paper, we propose the generation of an adaptive neuro-Fuzzy Inference System model using different clustering models such as a subtractive fuzzy clustering (SFC) model and a fuzzy c-mean clustering (FCM) model in the Takagi-Sugeno (TS) fuzzy model for selecting the hidden node centers. An experimental result on datasets of medical diagnoses shows the proposed model with two models of clustering (ANFIS-SFC & ANFIS-FCM) while comparing the …