Using mid-infrared and radio criteria, we select a sample of candidate z ∼ 2 obscured quasars. Optical spectroscopy confirms about half of these as type-2 quasars, and modelling the population suggests 50-80% of the quasars are obscured. We find some flat radio spectrum type-2 quasars, and tentative evidence for obscuration unrelated to the torus. Using a similar sample, we also find evidence f...

In this paper, we propose automatic generation methods of fuzzy classification rules with the Genetic Algorithms (GAs) to obtain compact fuzzy systems. This time, we propose an approach of hyper-cone membership function to construct rules for the antecedent part. Then, this method is determined the location and shape of hyper-cone membership function in the antecedent part, output class and the...

In this paper, we investigate majority rule with an infinite number of voters. We use an axiomatic approach and attempt to extend May’s Theorem characterizing majority rule to an infinite population. The analysis hinges on correctly generalizing the anonymity condition and we consider three different versions. We settle on bounded anonymity as the appropriate form for this condition and are abl...

The rule of sum says that the number of ways to choose an element from one of two disjoints sets is the sum of the cardinalities of the sets. That is, if A and B are two finite sets with no members in common, then |A ∪B| = |A|+ |B|. The rule of product says that the number of ways to choose an ordered pair is the number of ways to choose the first element from A and the second element from B. T...

Association rule discovery has emerged as an important problem in knowledge discovery and data mining. The association mining task consists of identifying the frequent item sets, and then forming conditional implication rules among them. Efficient algorithms to discover frequent patterns are crucial in data mining research. Finding frequent item sets is computationally the most expensive step i...

Association rule mining is a data mining technique that reveals interesting relationships in a database. Existing approaches employ different parameters to search for interesting rules. This fact and the large number of rules make it difficult to compare the output of confidence-based association rule miners. This paper explores the use of classification performance as a metric for evaluating t...

Among the computational intelligence techniques employed to solve classification problems, the fuzzy rule-based classification system (FRBCS) is a popular tool capable of building a linguistic model interpretable to users. However, it may face lack of accuracy in some complex applications, by the fact that the inflexibility of the concept of the linguistic variable imposes hard restrictions on ...

Rule mining is the practice of discovering interesting and unexpected rules from large data sets. Depending on the exact problem formulation, this may be a very complicated problem. Existing methods typically make strong simplifying assumptions about the form of the rules, and limit the measure of rule quality to simple properties, such as confidence. Because confidence in itself is not a good ...

In this paper, we discuss a method for decomposition, abstraction and reconstruction of the stochastic semantics of rule-based systems with conserved number of agents. Abstraction is induced by counting fragments instead of the species, which are the standard entities of information in molecular signaling. The rule-set can be decomposed to smaller rule-sets, so that the fragment-based dynamics ...