In order to avoid the over fitting and training and solve the knowledge extraction problem in fuzzy neural networks system.A lazylearning Dynamic Fuzzy Neural Network(LLDFNN) algorithm is *** learning Set based on La...
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In order to avoid the over fitting and training and solve the knowledge extraction problem in fuzzy neural networks system.A lazylearning Dynamic Fuzzy Neural Network(LLDFNN) algorithm is *** learning Set based on lazylearning is constituted from *** the framework of lazy Leaning Dynamic Fuzzy Neural Network is designed and its stability is ***,Simulation results of the three stage inverted pendulum system indicates that the novel lazylearning Dynamic Fuzzy Neural Network is fast,compact,capable in generalization.
In order to avoid the over rules and solve the knowledge extraction problem in fuzzy system. A novel variable universe fuzzy control based on lazy learning algorithm (LL-VUF) is firstly proposed in this paper. The Lea...
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ISBN:
(纸本)9783642226939
In order to avoid the over rules and solve the knowledge extraction problem in fuzzy system. A novel variable universe fuzzy control based on lazy learning algorithm (LL-VUF) is firstly proposed in this paper. The learning Set based on lazylearning is constituted from message. Then the new type function of contraction-expansion factor is designed based on lazy learning algorithm for temperature system. Finally, Simulation results of temperature regulating device indicates that the controller is fast, robust, capable in predict.
Outreach of internet has opened new horizons for the people who want quick and widespread dissemination of their ideas, and the tool to do so is blogging. Sloggers can broadly be classified into two groups: profession...
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Outreach of internet has opened new horizons for the people who want quick and widespread dissemination of their ideas, and the tool to do so is blogging. Sloggers can broadly be classified into two groups: professional and non-professional bloggers. As for professional bloggers, there are many factors that influence individuals to opt this profession. This study, with the help of an online dataset, attempts to identify such factors. Data analysis was made by using decision tree algorithms, lazy learning algorithms and ensembling methods. Nearest-neighbour classifier (IB1) and RandomForest have results with 85% accuracy and 84.8% precision for classification. The proof of concept is provided for result validation. The causes behind the varying performance of algorithms are elaborated. The factors that influence a blogger to behave professionally are identified based on the classifier with the best results. (C) 2017 Elsevier Ltd. All rights reserved.
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