Decision making and technical decision analysis demand computer-aided techniques and therefore more and more support by formal techniques. In recent years fuzzy decision analysis and related techniques gained importance as an efficient method for planning and optimization applications in fields like production planning, financial and economical modeling and forecasting or classification. It is ...

Data mining, as one of active fields nowadays, is to discover useful knowledge from large data sets. This paper focuses on continuous time-series data that have often been encountered in real applications (e.g., sales records, economic data, and stock transactions), and discusses how to discover the hidden relationship among time-series patterns in terms of their similarities. Fuzzy clustering ...

The paper proposes a new development method for a Takagi-Sugeno PI-fuzzy controller meant for a class of plants applicable to the fields of electrical drives or servo systems. The developed fuzzy control systems are quasi-optimal in terms of some quadratic performance indices defined in dynamic regimes with respect to the step modifications of the reference input and of four types of disturbanc...

We examine gauge theories on Minkowski space-time times fuzzy coset spaces. This means that the extra space dimensions instead of being a continuous coset space S/R are a corresponding finite matrix approximation. The gauge theory defined on this non-commutative setup is reduced to four dimensions and the rules of the corresponding dimensional reduction are established. We investigate in partic...

Analog design is quite more difficult than digital design. As a consequence, most of the effort in analog design still relies on designer’s experience. New ideas and methodogies are required to make a progress towards automating the analog design. Computational intelligence techniques, such as those based on fuzzy logic, have provided excellent results in those fields traditionally reserved to ...

Due to the frequent appearance of time series data in various fields, it has always been an essential and interesting research field. A time series analysis involves the methods for analyzing time series data, in order to mine meaningful and other relevant characteristics of the data. In most cases, time series data are quantitative values, so to come up with an intellectually appealing data mi...

This paper is the result of an interdisciplinary research between the marketing and the artificial intelligence fields. It briefly presents a brand new methodology to be applied in marketing (causal) modeling. Specifically, we apply it to a consumer behavior model used for the experimentation. The characteristics of the problem (with uncertain data and available knowledge from a marketing exper...

In the literature, there are a lot of methods concerning the problem of ordering the interval numbers k , ~ ] , [y,g], ... (', ') or the fuzzy ones A, B , ... (see 4, and for a n overview of methods). All of these methods can be classified a s belonging t o two different approaches. (i) Ordering t h e crisp or the fuzzy intervals using binary order relations: [ c , ~ ] 4 [ y , ~ ] , A 5 B, .......

Representing and consequently processing fuzzy data in standard and binary databases is problematic. The problem is further amplified in binary databases where continuous data is represented by means of discrete ‘1’ and ‘0’ bits. As regards classification, the problem becomes even more acute. In these cases, we may want to group objects based on some fuzzy attributes, but unfortunately, an appr...