in this paper, our focus of attention is the proper propagationof fuzzy degrees in determinization of $nondeterministic$ $fuzzy$$finite$ $tree$ $automata$ (nffta). initially, two determinizationmethods are introduced which have some limitations (one inbehavior preserving and other in type of fuzzy operations). inorder to eliminate these limitations and increasing theefficiency of ffta, we defin...

The proposed method develops a fuzzy rule-based classifier that was tested using features for islanding detection in distributed generation. In the developed technique, the initial classification boundaries are found out by using the decision tree (DT). From the DT classification boundaries, the fuzzy membership functions (MFs) are developed and the corresponding rule base is formulated for isl...

The work deals with a recognition problem using a probabilistic-fuzzy model and multistage decision logic. A case where a loss function is described using fuzzy numbers has been considered. The globally optimal Bayes strategy has been calculated for this case with stage-dependent and dependent on the node of the decision tree fuzzy loss function. The obtained result is illustrated by a calculat...

Voltage insecurity is a most vital problem that the modern power systems are imposed off. Timely and accurate assessment of voltage security is necessary to detect post-contingency voltage problems in order to prevent a large scale blackout. The paper presents machine learning techniques based on CART algorithm and probabilistic decision tree based strategy for estimation of voltage security. T...

This paper focuses on the study of the error composition of a fuzzy decision tree induction method recently proposed by the authors, called soft decision trees. This error may be expressed as a sum of three types of error: residual error, bias and variance. The paper studies empirically the tradeo between bias and variance in a soft decision tree method and compares it with the tradeo of classi...

Data mining can be said to have the aim to analyze the observational datasets to find relationships and to present the data in ways that are both understandable and useful. In this thesis, some existing intelligent systems techniques such as Self-Organizing Map, Fuzzy C-means and decision tree are used to analyze several datasets. The techniques are used to provide flexible information processi...

Advances in a fuzzy decision theory that allow automatic cooperation between unmanned aerial vehicles (UAVs) are discussed. The algorithms determine points the UAVs are to sample, flight paths, and the optimal UAVs for the task and related changes during the mission. Human intervention is not required after the mission begins. The algorithms take into account what is known before and during the...