The Mamdani and TSK fuzzy models are fuzzy inference engines which have been most widely applied in real-world problems. Compared to the Mamdani approach, the TSK approach is more convenient when the crisp outputs are required. Common to both approaches, when a given observation does not overlap with any rule antecedent in the rule base (which usually termed as a sparse rule base), no rule can ...

New methods, like fuzzy logic, are coming into the field of adaptive traffic signal control. Development of the fuzzy control can roughly be divided into two research approaches: development of fuzzy control functions, and development of fuzzy inference methods. Both approaches are discussed in this paper. First, a lately developed fuzzy inference method, called maximal fuzzy similarity, is int...

Localization is one of the most important research topics in the wireless sensor network applications. To improve the indoor localization accuracy, the centroid localization algorithm based on Mamdani fuzzy system has been adopted to attain the weight between sensor node and anchor node. This paper proposes a novel optimized input membership function by bat algorithm in fuzzy inference system u...

Mamdani Systems are very well known in the area of Fuzzy Control, where they have been, they are, and they will continue to be successfully used. Efforts to linguistically interpret Mamdani Systems as a method for inference in fuzzy logic have faced the difficulty of interpreting the output of such systems before defuzzification, which consists of an aggregation of normally truncated fuzzy sets...

Many researchers have been interested in approximation properties of fuzzy logic systems (FLS), which like neural networks can be seen as approximation schemes. Almost all of them tackled Mamdani fuzzy model, which was shown to have many interesting features. This paper aims to present alternatives for traditional inference mechanisms and CRI method. The most attractive advantage of these new m...

increasing development of engineering projects construction such as city subway needs appropriate investigation, management and control of groundwater. therefore, precise estimation of hydrogeological parameters such as hydraulic conductivity is the most important factor in studies and modeling of groundwater and geotechnical issues. in recent decades, various laboratory and field methods exist...

Many researchers have been interested in approximation properties of fuzzy logic systems (FLS), which like neural networks can be seen as approximation schemes. Almost all of them tackled Mamdani fuzzy model, which was shown to have many interesting features. This paper aims to present alternatives for traditional inference mechanisms and CRI method. The most attractive advantage of these new m...

Neuro-fuzzy computing, which provides efficient information processing capability by devising methodologies and algorithms for modeling uncertainty and imprecise information, forms at this juncture, a key component of soft computing. An integrated neuro-fuzzy system is simply a fuzzy inference system trained by a neural networklearning algorithm. The learning mechanism fine-tunes the underlying...

Diabetes is a situation when a body is not capable to produce insulin, which is needed to control glucose. Diabetes will also develop heart disease, kidney disease, blindness, nerve damage, and blood vessel damage. This paper uses Mamdani-type and Sugeno-type fuzzy expert systems for a diabetes diagnosis. Fuzzy expert system is a group of membership functions and rules. Fuzzy expert systems are...

In this study, the road traffic congestion of Dehradun city is evaluated from traffic flow information using fuzzy techniques. Three different approaches namely Sugeno, Mamdani models which are manually tuned techniques, and an Adaptive Neuo-Fuzzy Inference System (ANFIS) which an automated model decides the ranges and parameters of the membership functions using grid partition technique, based...