due to the high penetration of wind farms in the networks, they can have a significant role in the control of power systems. in this paper, wind farms (wfs) are used to improve the static security margins of the power system. generation rescheduling is one of the remedies to improve the static security margins of the power system. in this paper, the generation rescheduling is presented based on...

Fuzzy Decision Tree induction is a powerful methodology to extract human interpretable classification rules. The induction of fuzzy decision tree is done using popular Fuzzy ID3 algorithm [1, 2]. The other parameters which influence the performance of fuzzy decision tree are cut standard parameter  and leaf selection threshold parameter th  . Generally these parameters are to be selected heur...

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...

Purpose: Human biology is an essential field in scientific research as it helps understanding the human body for adequate care. Technology has improved way scientists do their biological research. One of critical technologies artificial intelligence (AI), which revolutionizing world. Scientists have applied AI studies, using several methods to gain different types data. Machine learning a branc...

Decision tree learning is a machine learning technique that allows us to generate accurate and comprehensible models. Accuracy can be improved by ensemble methods which combine the predictions of a set of different trees. However, a large amount of resources is necessary to generate the ensemble. In this paper, we introduce a new ensemble method that minimises the usage of resources by sharing ...

In this paper, first, an initial feature vector for vocal fold pathology diagnosis is proposed. Then, for optimizing the initial feature vector, a genetic algorithm is proposed. Some experiments are carried out for evaluating and comparing the classification accuracies which are obtained by the use of the different classifiers (ensemble of decision tree, discriminant analysis and K-nearest neig...