Adaptive Neuro-fuzzy inference system (ANFIS) is multi-layer system proposed by Jang, enables to increase the performance by integrates the best features of Artificial Neural Networks and Fuzzy inference system into a single framework. It is a popular framework for solving complex problems. In this present work, an ANFIS is proposed for detection the risk factor of hypertension. In this work, f...

The neuro-fuzzy controller incorporates fuzzy logic algorithm with an artificial neural network (ANN) structure. The conventional PI controller is replaced by Adaptive NeuroFuzzy Inference System (ANFIS), which tunes the fuzzy inference system with hybrid learning algorithm, This makes fuzzy system training with performance of the neuro-fuzzy based vector controlled of the system under controll...

Decision making pertaining to injection profiles during oilfield development is one of the most important factors that affect the oilfields’ performance. Since injection profiles are affected by multiple geological and development factors, it is difficult to model their complicated, non-linear relationships using conventional approaches. In this paper, two adaptivenetwork-based fuzzy inference ...

In this paper, a modified analysis of Four Wave Mixing (FWM) by incorporating the third-order dispersion parameters is reported. With the help of a modified formula for FWM crosstalk, the effect of secondand third-order dispersion parameters at different input channel powers has been analysed. Under the combined effect of secondand third-order dispersion parameters, the crosstalk introduced by ...

This paper presents an expert system for evaluation of the unemployed at certain offered posts. The expert application uses Neuro-Fuzzy techniques for analyzing a corporate database of unemployed and enterprises profile data. The process of matching an unemployed with an offered job is performed through a Sugeno type Neuro-Fuzzy inference system. Large training sets of old historical records of...

Robust parameter design has been successfully applied to a variety of engineering problems for enhancing the robustness of the system; however, it cannot deal with multiple dynamic quality systems. Although several other approaches have been presented to resolve this problem, they are unable to efficiently treat the situations that the control factors have continuous values. This study incorpor...