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SelectedWorks

R. W. Hndoosh

Articles 1 - 8 of 8

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 Oct 2014

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 …

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Fuzzy Mathematical Models For The Analysis Of Fuzzy Systems With Application To Liver Disorders, R.W. W. Hndoosh Oct 2014

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 …

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Fuzzy Mathematical Model For Detection Of Lung Cancer Using A Multi-Nfclass With Confusion Fuzzy Matrix For Accuracy, R.W. W. Hndoosh Sep 2014

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, …

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Mathematical Structure Of Fuzzy Modeling Of Medical Diagnoses By Using Clustering Models, R.W. W. Hndoosh Aug 2014

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 …

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A Proposition For Using Mathematical Models Based On A Fuzzy System With Application, R. W. Hndoosh Oct 2013

A Proposition For Using Mathematical Models Based On A Fuzzy System With Application, R. W. Hndoosh

R. W. Hndoosh

Some mathematical models based on fuzzy set theory, fuzzy systems and neural network techniques seem very well suited for typical technical problems. This study aims to build two different models, the Fuzzy Inference System (FIS) and the Adaptive Fuzzy System using neural network. We have proposed a new model of a fuzzy system that is extended from 2-dimensions to 3-dimensions, using Mamdani's minimum implication, the minimum inference system, the Singleton fuzzifier and the Center Average Defuzzifier. Also, we have extended the theorem accuracy of the fuzzy system to 3- dimensions along with changing the type of fuzzy inference system. We …

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Fuzzy And Adaptive Neuro-Fuzzy Inference System Of Washing Machine, R.W. Hndoosh Sep 2012

Fuzzy And Adaptive Neuro-Fuzzy Inference System Of Washing Machine, R.W. Hndoosh

R. W. Hndoosh

Software estimation accuracy is among the greatest challenges for software developers. Fuzzy set theory, Fuzzy system and Neural Networks techniques seem very well suited for typical technical problems. In conjunction with software computing and conventional mathematical methods, hybrid methods can be developed that may prove to be a step forward in modeling geotechnical problems. This study aimed at building two different models, Fuzzy Inference Systems and Adaptive Neuro Fuzzy Inference System and a comparison between them, through an application to real data of the relationship between three inputs (time, temperature of water and the amount of washing powder) during the …

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Using Clustering For Modeling Monthly Salary Grade, R. W. Hndoosh Jul 2010

Using Clustering For Modeling Monthly Salary Grade, R. W. Hndoosh

R. W. Hndoosh

Clustering is considered as one of the most scientifically developments which the scientists reached at in the field of recent knowledge and technologies to discover the cluster's group. The clustering concept was introduced firstly by Ronald in 1955. The clustering's fundamental notion is represented in dividing the data into clusters. This research aims to using clustering for actual data modeling for the monthly salary grade of the teaching staff for one of the Mosul University's College in 2009, by using HCM algorithm to these data. Matlab software is used to write down the proposed algorithm programs. Results proved the efficiency …

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The Application Of Fuzzy Logic To The Modeling Of Product Density For Children Ready-Made Clothes, R. W. Hndoosh Jun 2009

The Application Of Fuzzy Logic To The Modeling Of Product Density For Children Ready-Made Clothes, R. W. Hndoosh

R. W. Hndoosh

The main objective of this research is to design a program model for a new product density estimation by implementing fuzzy logic techniques. This model is designed depending upon some of the factors influencing product density. The model consists of conditional rules. Mamdani fuzzy inference system is used for reasoning process because it is an efficient type of fuzzy inference for knowledge to make decision processing. The model is designed using MATLAB as the programming tool for writing the model's programs. The model is applied to real data average taken from Mosul factory for children Ready-Made clothes. The results obtained …

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