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...

This paper explores the learning fuzzy inference systems implemented as adaptive fuzzy-neural networks. The research into application of learning techniques to fuzzy inference systems (FIS) has matured into a family of adaptive fuzzy inference systems (AFIS). In most cases, the learning FIS and AFIS families can be interpreted as a partially connected multilayer feedforward neural network with ...

This paper aims at helping to clarify the current confusion raised by a lot of workscomparing or merging neural net with fuzzy inference systems. On the theoretical side,we first show that a specific family of neural nets: Radial-Basis Functions (RBF) and aspecific family of fuzzy inference systems: Tagaki-Sugeno fuzzy inference systems (FIS)are nearly equivalent structure altho...

Fuzzy inference has been proven a candidate technology for context recognition systems. In comparison to probability theory, its advantage is its more natural mapping of phenomena of the real world as context. This paper reports on our experience with an building and using of monolithic fuzzy based system (a TSK-FIS) to recognize realworld events and to classify these events into several catego...

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...

This study describes the Failure Mode and Effects Analysis (FMEA) from the point of view of different artificial intelligence approaches. After discussing the main drawbacks of the traditional methodology and summarize the main techniques recommended for its improvement in the recent literature, three techniques of Artificial Intelligence are compared: a fuzzy inference system (FIS), a case rea...

Performance Appraisal is the systematic assessment of performance of employees to understand the abilities for further development. According to sixth pay commission the approach adopted for evaluation of teaching staff performance focuses on areas like Teaching, Learning, Extension, Research, Publication etc. which are actually fuzzy concepts that can be captured in fuzzy terms. In the propose...

abstract evapotranspiration as one of the most important components of the hydrologic cycle, plays a key role in water resources management, crop yield simulation and irrigation scheduling. therefore, presenting a low cost and precision model is very essential for calculations of hourly eto. although, there are empirical formulas, their performances are not all satisfactory due to the complicat...

Fuzzy inference has been proven a candidate technology for context recognition systems. In comparison to probability theory, its advantage is its more natural mapping of phenomena of the real world as context. This paper reports on our experience with building and using monolithic fuzzy-based systems (a TSK-FIS) to recognize real-world events and to classify these events into several categories...