System reliability assessment is one of the major acts in the operation and maintenance of every industrial and service sector, which also holds true for maritime transportation system. The complexity of the maritime transportation system is a prime obstacle in the evaluation of the operational reliability of the system; mainly due to the fact that statistical data on the important parameters a...

TnT is an efficient statistical Parts-of-speech (POS) Tagger based on Hidden Markov Model. TnT performs well on known word sequences. But, the performance degrades with increase in the number of unknown words. In this paper, we propose a method to overcome this performance degradation using fuzzy rules. Fuzzy rule based model is designed to provide TnT with sufficient information about the tag ...

In this study, the roll, yaw and depth fuzzy control of an Au- tonomous Underwater Vehicle (AUV) are addressed. Yaw and roll angles are regulated only using their errors and rates, but due to the complexity of depth dynamic channel, additional pitch rate quantity is used to improve the depth loop performance. The discussed AUV has four aps at the rear of the vehicle as actuators. Two rule bases...

One of the common problems for fuzzy system implementation arises from the complications of the fuzzy inference process. Extra computations are required to deduce a consequence due to nature of fuzzy sets. Furthermore, considerable simulations need to be performed to verify system functions. In order to reduce the prototyping time, the fuzzy system is partitioned into hardware and software port...

This paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. In this method, mammograms are segmented into regions of interest (ROI) in order to extract features including geometrical and contourlet coefficients. The extracted features benefit from...

Genetic fuzzy rule selection is an effective approach to the design of accurate and interpretable fuzzy rule-based classifiers. It tries to minimize the complexity of fuzzy rule-based classifiers while maximizing their accuracy by selecting only a small number of fuzzy rules from a large number of candidate rules. One important issue in genetic fuzzy rule selection is the prescreening of candid...

Our concern is with the determination of the firing level of the antecedent fuzzy set in a fuzzy systems model rule base. We first consider the case where the input information is also expressed in terms of a normal fuzzy set. We provide the requirements needed by any formulation of this operation. We next consider the case when the input information is expressed using a measure. Here we also p...

System modeling with fuzzy rule-based systems (FRBSs), i.e. fuzzy modeling (FM), usually comes with two contradictory requirements in the obtained model: the interpretability, capability to express the behavior of the real system in an understandable way, and the accuracy, capability to faithfully represent the real system. While linguistic FM (mainly developed by linguistic FRBSs) is focused o...

Fuzzy modeling has become very popular because of its main feature being the ability to assign meaningful linguistic labels to the fuzzy sets in the rule base. This paper examines Sugeno and Yasukawa’s qualitative modeling approach, and addresses one of the remarks in the original paper. We propose a cluster search algorithm that can be used to provide a better projection of the output space to...