Fuzzy logic and fuzzy systems have recently been receiving a lot of attention, both from the media and scientific community, yet the basic techniques were originally developed in the mid-sixties. Fuzzy logic provides a formalism for implementing expert or heuristic rules on computers, and while this is the main goal in the field of expert or knowledge-based systems, fuzzy systems have had consi...

Neuro-fuzzy systems have been in the focus of recent research as a solution to jointly exploit the main features of fuzzy logic systems and neural networks. Within the application literature, neuro-fuzzy systems can be found as methods for function identification. This approach is supported by theorems that guarantee the possibility of representing arbitrary functions by fuzzy systems. However,...

The major prevailing challenges for Software Projects are Software Estimations like cost estimation, effort estimation, quality estimation and risk analysis. Though there are several algorithmic cost estimation models in practice, each model has its own pros and cons for estimation. There is still a need to find a model that gives accurate estimates. This paper is an attempt to experiment diffe...

This paper implements a Neuro-Fuzzy (FNN) approach to autonomously navigate a car-like robot in an unknown environment. The applied technique allows the robot to avoid obstacles and locally search for a path leading to the goal after learning and adaptation. It is based on two Fuzzy Artmap neural networks, a Reinforcement trial and error neural network and a Mamdani fuzzy logic controller (FLC)...

-In this paper, we analyze the impact of extinction ratio (Ron/off) of Mach-Zehnder (MZ) amplitude modulator using Fuzzy logic generator. The system performance has been analyzed by varying the value of extinction ratio (Ron/off) from 0 to 10 dB. It is found that the system gives optimum performance at extinction ratio value 9.965 dB. Further, the fuzzy model of the system is developed using AN...

We introduce Riesz Logic, whose models are abelian lattice ordered groups, which generalise Riesz spaces (vector lattices), and show soundness and completeness. Our motivation is to provide a logic for distributional semantics of natural language, where words are typically represented as elements of a vector space whose dimensions correspond to contexts in which words may occur. This basis prov...

Computer aided diagnosis systems for detecting malignant texture in biological study have been investigated using several techniques. This paper presents an approach in computer-aided diagnosis for early prediction of brain cancer using Texture features and neuro classification logic. The Tumor mass detection and Cluster micro classification is used as the processing method for cancer predictio...

Electrocardiogram is used to measure the rate and regularity of heartbeats to detect any irregularity to the heart. An ECG translates the heart electrical activity into wave-line on paper or screen. For the feature extraction and classification task we will be using discrete wavelet transform (DWT) as wavelet transform is a two-dimensional timescale processing method, so it is suitable for the ...

This paper presents a hybrid model for predicting the occurrence of currency crises by using the neuro fuzzy modeling approach. The model integrates the learning abil i ty of neural network with the inference mechanism of fuzzy logic . The empirical results show that the proposed neuro fuzzy model leads to a better prediction of crisis . Significantly, the model can also construct a rel iable c...

With their significant advantages over traditional electromagnetic motors, ultrasonic motors (USMs) are becoiming attractive. This paper presents a neuro-fuzzy dualmode controller, combining the knowledge-based fuzzy logic and the leaming-incorporated neural network as well as using dual control inputs, for servo control of travelling-wave USMk. According to the proposed neuro-fuzzy control, bo...