Open Access
The Prediction Algorithm Based on Fuzzy Logic Using Time Series Data Mining Method
TLDR
In this paper, a prediction algorithm using time series data mining based on fuzzy logic is proposed and truth of prediction algorithm based fuzzy logic has been proved by application results.Abstract:
Prediction of an event at a time series is quite important for engineering and economy problems. Time series data mining combines the fields of time series analysis and data mining techniques. This method creates a set of methods that reveal hidden temporal patterns that are characteristic and predictive of time series events. Time series data mining examines the time series in a phase space. In this paper, a prediction algorithm using time series data mining based on fuzzy logic is proposed. Earthquake prediction has been done from a synthetic earthquake time series by using investigating method at first step ago. Time series has been transformed to phase space by using nonlinear time series analysis and then fuzzy logic has been used to prediction optimal values of important parameters characterizing the time series events. Truth of prediction algorithm based fuzzy logic has been proved by application results.read more
Citations
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Nonlinear Time Series Analysis.
TL;DR: This thesis applies neural network feature selection techniques to multivariate time series data to improve prediction of a target time series and results indicate that the Stochastics and RSI indicators result in better prediction results than the moving averages.
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Data-Driven Techniques in Disaster Information Management
Tao Li,Ning Xie,Chunqiu Zeng,Wubai Zhou,Li Zheng,Yexi Jiang,Yimin Yang,Hsin-Yu Ha,Wei Xue,Yue Huang,Shu-Ching Chen,Jainendra K. Navlakha,S. Sitharama Iyengar +12 more
TL;DR: A general overview of the requirements and system architectures of disaster management systems is presented and state-of-the-art data-driven techniques that have been applied on improving situation awareness as well as in addressing users’ information needs in disaster management are summarized.
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A review on application of data mining techniques to combat natural disasters
TL;DR: An extensive and in-depth literature study on current techniques for disaster prediction, detection and management has been done and the results are summarized according to various types of disasters.
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ClusFuDE: Forecasting low dimensional numerical data using an improved method based on automatic clustering, fuzzy relationships and differential evolution
TL;DR: The proposed ClusFuDE method uses an improved automatic clustering approach for clustering the historical numerical data and provides the lowest MSE and MAPE when compared to all other methods available in the literature.
References
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Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Book
Data Mining: Concepts and Techniques
TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.
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Neural network design
TL;DR: This book, by the authors of the Neural Network Toolbox for MATLAB, provides a clear and detailed coverage of fundamental neural network architectures and learning rules, as well as methods for training them and their applications to practical problems.
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Nonlinear time series analysis
Holger Kantz,Thomas Schreiber +1 more
TL;DR: Using nonlinear methods when determinism is weak, as well as selected nonlinear phenomena, is suggested to be a viable alternative to linear methods.
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