Fuzzy systems, neural networks and its combination in neuro-fuzzy systems are already well established in data analysis and system control. Especially, neurofuzzy systems are well suited for the development of interactive data analysis tools, which enable the creation of rule-based knowledge from data and the introduction of a-priori knowledge into the process of data analysis. However, its rec...

Two methods for the extension of neuro-modules are introduced resulting in a new behavioral functionality. We call them restricted and semi-restricted module expansion. These methods are developed and applied using a modular neuro-dynamics approach to behavior control of autonomous mobile robots. Evolved neuro-controllers which solve an obstacle avoidance task are expanded to show in addition a...

security term in mobile ad hoc networks has several aspects because of the special specification of these networks. in this paper a distributed architecture was proposed in which each node performed intrusion detection based on its own and its neighbors’ data. fuzzy-neural interface was used that is the composition of learning ability of neural network and fuzzy ratiocination of fuzzy system as...

In the Internet of Things (IoT) equipment used for aquaculture is often deployed in outdoor ponds located in remote areas. Faults occur frequently in these tough environments and the staff generally lack professional knowledge and pay a low degree of attention in these areas. Once faults happen, expert personnel must carry out maintenance outdoors. Therefore, this study presents an intelligent ...

The paper presents a comparison of various soft computing techniques used for filtering and enhancing speech signals. The three major techniques that fall under soft computing are neural networks, fuzzy systems and genetic algorithms. Other hybrid techniques such as neuro-fuzzy systems are also available. In general, soft computing techniques have been experimentally observed to give far superi...

We investigate local robust stability of fuzzy neural networks FNNs with time-varying and S-type distributed delays. We derive some sufficient conditions for local robust stability of equilibrium points and estimate attracting domains of equilibrium points except unstable equilibrium points. Our results not only show local robust stability of equilibrium points but also allow much broader appli...

This paper studies traffic variable estimation, and presents a method of estimation for the number of vehicle waiting for queue (NVWQ) based on neuro-fuzzy at urban intersection. we present results of training the neural network for a detectorized intersection in Changsha City. The accuracy of NVWQ estimation using the fuzzy neural networks approaches is more than 90%. The fuzzy neural networks...

Various artificial neural networks types are examined and compared for the prediction of surface roughness in manufacturing technology. The aim of the study is to evaluate different kinds of neural networks and observe their performance and applicability on the same problem. More specifically, feed-forward artificial neural networks are trained with three different back propagation algorithms, ...

The investigation of solar-like oscillations for probing the star interiors has encountered a tremendous growth in the last decade. For ground based observations the most important difficulties in properly identifying the true oscillation frequencies of the stars are produced by the gaps in the observation time-series and the presence of atmospheric plus the intrinsic stellar granulation noise,...