Eagle was introduced as a general purpose rule-based temporal logic for specifying run-time monitors. A novel and relatively efficient interpretative trace-checking scheme via stepwise transformation of an Eagle monitoring formula was defined and implemented. However, application in real-world examples has shown efficiency weaknesses, especially those associated with large-scale symbolic formul...

A recent resurgence in logical-rule theories of categorization has motivated the development of a class of models that predict not only choice probabilities but also categorization response times (RTs; Fifić, Little, & Nosofsky, 2010). The new models combine mental-architecture and random-walk approaches within an integrated framework and predict detailed RT-distribution data at the level of in...

The simpliied pure literal algorithm solves satissability problems by c hoosing variables in a xed order and then generating subproblems for various values of the chosen variable. If some value satisses every relation that depends on the chosen variable, then only the subproblem for that preferred value is generated. Otherwise, a subproblem is generated for every value of the variable. The full...

A significant limitation of neural networks is that the representations they learn are usually incomprehensible to humans. We have developed an algorithm, called TREPAN, for extracting comprehensible, symbolic representations from trained neural networks. Given a trained network, TREPAN produces a decision tree that approximates the concept represented by the network. In this article, we discus...

To deal with severe drought when water supply is insufficient hedging rule, based on hedging rule curve, is proposed. In general, in discrete hedging rules, the rationing factors have changed from a zone to another zone at once. Accordingly, this paper is an attempt to improve the conventional hedging rule to control the changes of rationing factors. In this regard, the simulation model has emp...

There are many methods introduced to solve the credit scoring problem such as support vector machines, neural networks and rule based classifiers. Rule bases are more favourite in credit decision making because of their ability to explicitly distinguish between good and bad applicants.In this paper multi-objective particle swarm is applied to optimize fuzzy apriori rule base in credit scoring. ...

The generation of effective feature-based rules is essential to the development of any intelligent system. This paper presents an approach that integrates a powerful fuzzy rule generation algorithm with a rough set-assisted feature reduction method to generate diagnostic rule with a certainty factor. Certainty factor of each rule is calculated by considering both the membership value of each li...

mulla sadra, as the founder of the transcendental philosophy, has special viewpoints on society. unlike those who believe that mulla sadra ignored society and paid his mere attention to the spiritual issues, he cared about the social situation of his time and proposed certain pathological guidelines to reform the society. in his opinion, the real problem was that those who truly deserved to rul...