This paper describes links between computational intelligence (CI), data mining and knowledge discovery. The generating elements of soft computing based data mining algorithms are defined where the extracted knowledge is represented by fuzzy rule-based expert systems. It is recognized that both model performance and interpretability are of major importance, and effort has to make to keep the re...

Now-a-days medical domain is a popular area for the artificial intelligence (AI) research. Many of the early AI systems were attempted to apply rule-based reasoning in developing computer-based diagnosis system in medical domain. However, for a broad and complex medical domain the effort of applying rule-based system has encountered several problems. Today many systems are serving multi-purpose...

An effective way to cope with classification problems, among others, is by using Fuzzy Rule-Based Classification Systems (FRBCSs). These systems are composed two main components, the Knowledge Base (KB) and Reasoning Method (FRM). The FRM responsible for performing of new examples based on information stored in KB. A key point how given fired fuzzy rules aggregated. Precisely, aggregation funct...

Article history: Received February 25, 2016 Received in revised format: March 28, 2016 Accepted June 26, 2016 Available online June 26 2016 Weather forecasting is essential and demanding scientific task of meteorological services across the world. It is a complex procedure that includes many specific technological field of study. The prediction is intricate process in meteorology because all de...

In regression problems, the use of TSK fuzzy systems is widely extended due to the precision of the obtained models. Moreover, the use of simple linear TSK models is a good choice in many real problems due to the easy understanding of the relationship between the output and input variables. In this paper we present FRULER, a new genetic fuzzy system for automatically learning accurate and simpl...

In this paper we present a new fuzzy reasoning method in which the Choquet integral is used as aggregation function. In this manner, we can take into account the interaction among the rules of the system. For this reason, we consider several fuzzy measures, since it is a key point on the subsequent success of the Choquet integral, and we apply the new method with the same fuzzy measure for all ...

In the last thirty years fuzzy logic became very popular. One can find solutions based on it in several fields from industrial systems to house appliances. Recently a new category of fuzzy systems gained more attention, the so called fuzzy rule interpolation (FRI) based systems. Owing to the low complexity of their rule bases, i.e. they can infer as well when only the relevant rules are known, ...

Reasoning with fuzzy rule-based models has been widely applied to perform various real world classification tasks. The main advantage of this approach is that it supports inferences in the way people think and make judgements. However, in order to gain high classification accuracy, transparency and interpretability of such models has often been ignored. To counter against this limitation, this ...

Both crisp and fuzzy rule-based expert systems are increasingly used in the real-time environments. For both types of systems the stability and nite response time are required. It is therefore crucial for both to provide tools that perform stability analysis. This paper shows how the analysis tools built for crisp real-time rule-based system might be used for fuzzy systems as well. Major diiere...