Plant monitoring and diagnosis are usually integrated as one process to detect and isolate suspicious symptoms and use these to identify the root cause of the failure [1, 2]. The research reported here enables a new plant monitoring and diagnosis framework that employs multiple fuzzy rule-based decision-support system at different diagnosing stages. By employing fuzzy sets and by constructing a...

W. Senn1;2, M. Jakob2, K. Wyler2, J. Kleinle2, H.-R. L uscher3, H. Mey2, L. M uller2 Abstract | Methods of fuzzy logic are commonly used to model a complex system by a set of rules provided by experts. But fuzzy methods can also be applied to the reverse problem: given the inputoutput behavior of a system, what are the rules which are governing that behavior. We introduce this reengineering m...

This paper unifies theories of fuzzy systems, cognition, economic man and organization behavior in order to introduce cognitive machines. It contributes by outlining the impact of fuzzy theory on these fields which have been subject of Nobel Prize in Economics. This research advocates and explains that Fuzzy Theory involves the necessary mathematical and logical foundations which materialize th...

This paper describes fuzzy logic approach to mobile robot behavior design. An autonomous mobile robot must be able to move safely in a crowded unknown environment for reaching a desired goal. A successful way of structuring the navigation task in order to deal with the problem is within behavior based navigation approaches. In this paper, individual behavior design will be addressed using fuzzy...

A fuzzy-modeling method for the emulation of expert decision behavior for static as well as dynamic systems is presented. The input – output dataset of the system – or expert behavior is changed using fuzzy-sets into examples in linguistic form. These resulting examples build the fundament of the machine learning process for rule production (ID3).

The extraction of models from data streams has become a hot topic in data mining due to the proliferation of problems in which data are made available online. This has led to the design of several systems that create data models online. A novel approach to online learning of data streams can be found in Fuzzy-UCS, a young Michiganstyle fuzzy-classifier system that has recently demonstrated to b...

This paper presents a string matching experience using deformed fuzzy automata for the recognition of imperfect strings. We propose an algorithm based on a deformed fuzzy automaton that calculates a similarity value between strings having a non-limited number of edition errors. Different selections of the fuzzy operators for computing the deformed fuzzy automaton transitions allows to obtain di...

background: there are many studies to investigate the effects of each interacting component of tumor-immune system interactions. in all these studies, the distinct effect of each component was investigated. as the interaction of tumor-immune system has feedback and is complex, the alternation of each component may affect other components indirectly. objective: because of the complexities of tum...

In this paper we suggest that social robots should not mirror exactly human social behavior (facial expressions, language, etc) but need to be able to produce believable social behaviors that provide a minimal set of actions by which human-companion cooperation can be achieved. For implementing such an ethologically inspired social robot behavior, a platform based on fuzzy automaton (fuzzy stat...

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.