Topic
Decision tree model
About: Decision tree model is a research topic. Over the lifetime, 2256 publications have been published within this topic receiving 38142 citations.
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01 Feb 2018
TL;DR: In this paper, transient stability assessment is performed on a power system using a classification approach and data mining algorithms using offline training data collected by conducting load flow studies under normal operating conditions and faulty operating conditions at buses, at three different locations at lines and at different load levels.
Abstract: In this paper, transient stability assessment is performed on a power system using a classification approach and data mining algorithms. As a first step, offline training data was collected by conducting load flow studies under normal operating conditions and faulty operating conditions at buses, at three different locations at lines and at different load levels. Twenty-three features were chosen to represent the training data for each load flow simulation. A support vector machine model was built and trained using the training data as well as a Naive Bayes model and Decision Tree model. Then an online testing model was developed and real-time data was used to test the validity of the model developed. The results indicate a higher accuracy and less time consumed by the core vector machine model compared to previous models available in literature. The IEEE 14 bus system was used for training data and for verifying the speed and accuracy of the proposed data mining algorithm.
12 citations
TL;DR: It is shown that if f can be represented in k-DNF form and in j-CNF form, then O(n log(min(k, j)/q) queries suffice to compute f with error probability less than q, where n is the number of input bits.
Abstract: We consider the problem of computing with faulty components in the context of the Boolean decision tree model, in which cost is measured by the number of input bits queried, and the responses to queries are faulty with a fixed probability. We show that if f can be represented in k-DNF form and in j-CNF form, then O(n log(min(k, j)/q)) queries suffice to compute f with error probability less than q, where n is the number of input bits. © 1994 John Wiley & Sons, Inc.
12 citations
TL;DR: To solve the multi-class fault diagnosis tasks, decision tree support vector machine (DTSVM), which combines SVM and decision tree using the concept of dichotomy, is proposed, which has better performance and higher generalization ability than the two conventional methods.
12 citations
TL;DR: The Self-Organizing feature Map neural network is applied to establish the predictive model of lithology for the K-Means optimized data set and the decision tree and support vector machine are utilized to process four new wells in the complicated Carboniferous reservoirs of the Wucaiwan Sag, eastern Junggar Basin.
12 citations