Terrorism has led to many problems in Thai societies, not only property damage but also civilian casualties. Predicting terrorism activities in advance can help prepare and manage risk from sabotage by these activities. This paper proposes a framework focusing on event classification in terrorism domain using fuzzy inference systems (FISs). Each FIS is a decisionmaking model combining fuzzy log...

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The primary goal of the study presented in this paper is to develop a novel and comprehensive approach to decision making using fuzzy discrete event systems (FDES) and to apply such an approach to real-world problems. At the theoretical front, we develop a new control architecture of FDES as a way of decision making, which includes a FDES decision model, a fuzzy objective generator for generati...

In daily life environmental sounds that are present around us include intricately mixed sounds emitted from different sources. This work aim is to contribute a method for sound source separation by means of the enhanced k-means clustering with adaptive genetic algorithm. At first removes the features from the input audio signal by means of Mel Frequency Cepstral Coefficients (MFCC) and spectral...

The paper presents our intermediate results in ontologizing a refined formal representation of environments, events, and happenings elaborated in PSI project. Our formal approach is based on the first order logic and is inspired by Discrete Event Calculus (DEC). In difference to DEC based on discrete linear time representation, it uses fuzzy time intervals [7]. Our framework also refines classi...

Timely faults detection in an industrial process is a key aspect for designing a framework for intelligent supervisory control. A way to perform supervisory control is by providing intelligence to the supervision mechanism in continuous processes exposed to faults in order to cope with the identification of a diversity of faults, classify them and to be able to anticipate the consequences deriv...

Abstract: Event tree is a logical analysis of probability for outcome events by initiating event and probable subsequent events. However, the evaluation of every single event may contain vague information or cannot be described by a crisp number of probabilities in application. So this paper aims to develop an event tree by using fuzzy set theory with a combination of triangle membership functi...

Probabilistic fuzzy systems combine a linguistic description of the system behaviour with statistical properties of data. It was originally derived based on Zadeh’s concept of probability of a fuzzy event. Two possible and equivalent additive reasoning schemes were proposed, that lead to the estimation of the output’s conditional probability density. In this work we take a complementary approac...

Triggers (active rules) bring domain-specific reactive behavior to databases. Traditional Event-Condition-Action triggers use only crisp concepts. In this paper, fuzzy triggers are proposed whereby approximate reasoning may be integrated with a traditional crisp database. The new approach paves the way for intuitive expression of application semantics of imprecise nature in database-bound appli...