This paper discusses the application of support vector machine in the area of identification of nonlinear dynamical systems. The aim of this paper is to identify suitable model structure for nonlinear dynamic system. In this paper, Adaptive Neuro Fuzzy Inference Systems (ANFIS) and Support Vector Regression (SVR) models are applied for identification of highly nonlinear dynamic process. The res...

This paper presents novel GA-ANFIS expert system prototype for dermatological disease detection by using dermatological features and diagnoses collected in real conditions. Nine dermatological features are used as inputs to classifiers that are based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for the first level of fuzzy model optimization. After that, they are used as inputs in Genetic ...

the uv-spectrophotometric method of analysis was proposed for simultaneous determination of fluoxetine (flx) and sertraline (srt). considering the strong spectral overlap between uv-vis spectra of these compounds, a previous separation should be carried out in order to determine them by conventional spectrophotometric techniques. here, full-spectrum multivariate calibrations adaptive neuro-fuzz...

Cancer research is one of the major research areas in the medical field. Adaptive Neuro Fuzzy Interference System is used for the classification of Cancer. This algorithm compared with proposed algorithm of Adaptive Neuro Fuzzy Interference system with Runge Kutta learning method for the best classification of cancer. It is one of the better techniques for the classification of the cancer. The ...

Original scientific paper This paper proposes a Neuro-fuzzy system for quantitative assessment of the effects of intelligent transportation systems and technologies on road fatalities. The basic idea in developing Neuro-fuzzy system is the fact that intelligent transportation systems and technologies activate some safety mechanisms and in turn the activation of safety mechanisms will have a pos...

This paper introduces the application of the hybrid approach Adaptive Neuro-Fuzzy Inference System (ANFIS) for fault classification and diagnosis in industrial actuator. The ANFIS can be viewed either as a fuzzy inference system, a neural network or fuzzy neural network (FNN). This paper integrates the learning capabilities of neural network to the robustness of fuzzy systems in the sense that ...

short term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. although various methodologies have been applied to forecast traffic parameters, several researchers have showed that compared with the individual methods, hybrid methods provide more accurate results . these results made the hybrid tools and approaches a more common method for ...

This paper introduces the application of the hybrid approach Adaptive Neuro-Fuzzy Inference System (ANFIS) for fault classification and diagnosis in industrial actuator. The ANFIS can be viewed either as a fuzzy inference system, a neural network or fuzzy neural network (FNN). This paper integrates the learning capabilities of neural network to the robustness of fuzzy systems in the sense that ...

Terrorism has led to many problems in Thai societies, not only property damage but also civilian casualties. Predicting terrorism activities in advance can help prepare and manage risk from sabotage by these activities. This paper proposes a framework focusing on event classification in terrorism domain using fuzzy inference systems (FISs). Each FIS is a decisionmaking model combining fuzzy log...

This chapter discusses the foundation of neuro-fuzzy systems. First, we introduce Takagi, Sugeno, and Kang (TSK) fuzzy model [l,2] and its difference from the Mamdani model. Under the idea of TSK fuzzy model, we discuss a neuro-fuzzy system architecture: Adaptive Network-based Fuzzy Inference System (ANFIS) that is developed by Jang [3]. This model allows the fuzzy systems to learn the paramete...