Operation of multi-reservoir systems is known as complicated and often large-scale optimization problems. The problems, because of broad search space, nonlinear relationships, correlation of several variables, as well as problem uncertainty, are difficult requiring powerful algorithms with specific capabilities to be solved. In the present study a Self-adaptive version of Melody Search algorith...

A rule-based system is a series of if-then statements that utilizes a set of assertions, to which rules are created on how to act upon those assertions. Rule-based systems often construct the basis of software artifacts which can provide answers to problems in place of human experts. Such systems are also referred as expert systems. Rule-based solutions are also widely applied in artificial int...

A set of ordered rules for generating variants of a variable determines (a) underlying/surface distinctions among some of the variants and (b) a hierarchical classification of the variants. In the analytical framework of variable rules, frequency data on variant occurrences in context bear only on (b) and not on (a). We provide a combinatorial characterization and enumeration of the set of clas...

Model trees—decision trees with linear models at the leaf nodes—have recently emerged as an accurate method for numeric prediction that produces understandable models. However, it is known that decision lists—ordered sets of If-Then rules—have the potential to be more compact and therefore more understandable than their tree counterparts. We present an algorithm for inducing simple, accurate de...

The two dominant schemes for rule learning C and RIPPER both operate in two stages First they induce an initial rule set and then they re ne it using a rather com plex optimization stage that discards C or adjusts RIPPER individual rules to make them work better together In con trast this paper shows how good rule sets can be learned one rule at a time with out any need for global optimization ...

Methods of fuzzy rule extraction based on rough set theory are rarely reported in incomplete intervalvalued fuzzy information systems. This paper deals with such systems. Instead of obtaining rules by attribute reduction, which may have a negative effect on inducting good rules, the objective of this paper is to extract rules without computing attribute reducts. The data completeness of missing...

The rule-generating abduction is a kind of abduction which generates a rule and proposes a hypothesis from a surprising fact . In general, there may exist in nitely many rules and hypotheses to explain such a surprising fact. Hence, we need to put some restriction on the class of rules. In rule-generating abduction, only one surprising fact is given. Hence, we also need to generalize the concep...

Fuzzy rule-based classification systems have been used extensively in data mining. This paper proposes a fuzzy rulebased classification algorithm based on a quantum ant optimization algorithm. A method of generating the hierarchical rules with different granularity hybridization is used to generate the initial rule set. This method can obtain an original rule set with a smaller number of rules....