نتایج جستجو برای: mamdani fuzzy inference model
تعداد نتایج: 2230636 فیلتر نتایج به سال:
This paper presents clustering techniques (K-means, Fuzzy K-means, Subtractive) applied on specific databases (Flower Classification and Mackey-Glass time series) , to automatically process large volumes of raw data, to identify the most relevant and significative patterns in pattern recognition, to extract production rules using Mamdani and Takagi-SugenoKang fuzzy logic inference system types.
The requirement to improve software productivity has promoted the research on software metrics technology. Object Oriented paradigm is the technology being used to build fault free and stupendous softwares; and to make them fault free object oriented metrics are being used. These metrics are used to identify high risk components early in the design phase and hence help us to reduce the rework a...
The aim of this work is to evaluate the effectiveness of a Simple Tuning algorithm applied on a Fuzzy Pulse Width Modulation controller in a real situation with DC gear motors. The fuzzy logic model proposed to control motor’s no-load speed consists in 25 rules based on Mamdani Fuzzy Inference System. A hardware implementation and an interface are designed for controlling the plant. In addition...
Modeling of the plant growth can be visualized using the approach of Lindenmayer System (L-System). This L-System models the plants growth by following the production rules, which are the combination of grammar and mathematic formulae. In this paper, we propose the use of fuzzy mamdani, to model the plant growth based on the current environment condition. The varied amount of fertilizer, both o...
fuzzy expert systems are one of the most practical intelligent models with the high potential for managing uncertainty associated to the medical diagnosis. in this paper, a fuzzy inference system (fis) for diagnosing of acute lymphocytic leukemia in children has been introduced. the fuzzy expert system applies mamdani reasoning model that has high interpretability to explain system results to e...
Fuzzy expert systems are one of the most practical intelligent models with the high potential for managing uncertainty associated to the medical diagnosis. In this paper, a fuzzy inference system (FIS) for diagnosing of acute lymphocytic leukemia in children has been introduced. The fuzzy expert system applies Mamdani reasoning model that has high interpretability to explain system results to e...
Mamdani fuzzy models have always been used as black-box models. Their structures in relation to the conventional model structures are unknown. Moreover, there exist no theoretical methods for rigorously judging model stability and validity. I attempt to provide solutions to these issues for a general class of fuzzy models. They use arbitrary continuous input fuzzy sets, arbitrary fuzzy rules, a...
Development of Load sensor is done in this paper, the input output of the load sensor is taken from the optical fiber sensor and the inputs are load and displacement and output is voltage. Load sensor is implemented by using two models i.e. mamdani fuzzy model and neuro fuzzy model and both the models are simulated using MATLAB, Fuzzy logic Toolbox and the results of the two models are compared...
The objective of our study is to design fuzzy expert system to diagnose the jaundice. To diagnose the jaundice both Mamdani and Sugeno fuzzy expert system is used. The symptoms of the jaundice are fed as inputs of fuzzy inference system and the outputs, i.e. grade of disease, is obtained. The grade is obtained using the fuzzy tool in MATLAB R2007a software. Ten patients of different ages and ge...
Fuzzy expert systems are one of the most practical intelligent models with the high potential for managing uncertainty associated to the medical diagnosis. In this paper, a fuzzy inference system (FIS) for diagnosing of acute lymphocytic leukemia in children has been introduced. The fuzzy expert system applies Mamdani reasoning model that has high interpretability to explain system results to e...
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