Navigation and obstacle avoidance are very important issues for the successful use of an autonomous mobile robot. To allow the robot to move between its current and final configurations without any collision within the surrounding environment, motion planning needs much treatment. Thus to generate collision free path it should have proper motion planning as well as obstacle avoidance scheme. Th...

this paper presents the bio-inspired neurofuzzy based route selection system to avoid traffic congestion. The proposed neuro-fuzzy system selects the best multi-parameters direction between two desired nodes: source and the endpoint. This research practices a mixture of neuro-fuzzy logic and ant colony system (ACS) algorithm for the principal routing to fulfill all the preferred requirements of...

The paper presents a new approach to fuzzy classification in the case of missing data. Rough-fuzzy sets are incorporated into logical type neuro-fuzzy structures and a rough-neuro-fuzzy classifier is derived. Theorems which allow determining the structure of the rough-neuro-fuzzy classifier are given. Several experiments illustrating the performance of the roughneuro-fuzzy classifier working in...

In this Review paper we discussed, how soft computing to the field of behavior based robotics. It discusses the role of fuzzy, neuro-fuzzy and genetic algorithm rule-based systems for behavior architectures and adaptation. It reviews a number of applications of soft computing techniques to autonomous robot navigation and control.

This paper describes application of information granulation theory, on the analysis of hydrocyclone perforamance. In this manner, using a combining of Self Organizing Map (SOM) and Neuro-Fuzzy Inference System (NFIS), crisp and fuzzy granules are obtained(briefly called SONFIS). Balancing of crisp granules and sub fuzzy granules, within non fuzzy information (initial granulation), is rendered i...

In this paper, we investigate an advanced monitoring system for a neonatal intensive care unit. The system intelligently detects abnormal neonatal cerebral Doppler ultrasound signals by means of principal component analysis and a non-normalised compensatory neuro-fuzzy rule based algorithm. Two hundred and ninety Doppler ultrasound signals were recorded from the anterior cerebral arteries of 40...

Function Points is an important and well-accepted software size metric. However, it is absolutely essential to accurately calibrate Function Point (FP), whose aims are to fit specific software application, to reflect software industry trend, and to improve cost estimation. Neuro-Fuzzy is a technique that incorporates the learning ability from neural network and the ability to capture human know...

This paper addresses the fault detection of a cracked cantilever beam using a hybrid artificial intelligence technique. The hybrid technique used here uses a fuzzy-neuro controller. The fuzzy-neuro controller has two parts. The first part is comprised of the fuzzy controller, and the second part is comprised of the neural controller. The input parameters of the fuzzy controller are relative dev...

This paper deals problem of intelligent hybrid systems. Intelligent systems include neural networks (NN), fuzzy systems (FS) and genetic algorithms (GA). Each of these intelligent systems has certain properties (ability of learning, modelling, classifying, obtaining empirical rules, solving optimizing tasks ...) fitting specific kind of applications. Combination of these intelligent systems cre...