A novel prediction method of complex univariate time series based on k-means clustering

[1]  David Sankoff,et al.  Distinguishing successive ancient polyploidy levels based on genome-internal syntenic alignment , 2019, BMC Bioinformatics.

[2]  Jie Zhang,et al.  LSTM-EFG for wind power forecasting based on sequential correlation features , 2019, Future Gener. Comput. Syst..

[3]  Changzhen Hu,et al.  Predicting blood pressure from physiological index data using the SVR algorithm , 2019, BMC Bioinformatics.

[4]  Heeyoul Choi.  Persistent Hidden States and Nonlinear Transformation for Long Short-Term Memory , 2019, Neurocomputing.

[5]  Zhen Liu,et al.  DBS: a fast and informative segmentation algorithm for DNA copy number analysis , 2019, BMC Bioinformatics.

[6]  Ha Young Kim,et al.  ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module , 2018, Expert Syst. Appl..

[7]  A. Bustamam,et al.  Implementation χ–sim co-similarity and agglomerative hierarchical to cluster gene expression data of lymphoma by gene and condition , 2018 .

[8]  Implementation of co-similarity measure on microarray data of lymphoma using K-means partition algorithm , 2018 .

[9]  Shou-De Lin,et al.  A Memory-Network Based Solution for Multivariate Time-Series Forecasting , 2018, ArXiv.

[10]  Haiping Wu,et al.  Multi-step wind speed forecasting using EWT decomposition, LSTM principal computing, RELM subordinate computing and IEWT reconstruction , 2018, Energy Conversion and Management.

[11]  Jian Zhou,et al.  Echo State Network with Multiple Loops Reservoir and its Application in Network Traffic Prediction , 2018, 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design ((CSCWD)).

[12]  Li Tang,et al.  PANK-A financial time series prediction model integrating principal component analysis, affinity propagation clustering and nested k-nearest neighbor regression , 2018 .

[13]  Hong-Sen Yan,et al.  PRODUCT PRICE FORECASTING BASED ON CORRELATIVE PRICE NET AND NEURAL NETWORKS , 2017 .

[14]  Suryakanth V. Gangashetty,et al.  Deep Elman recurrent neural networks for statistical parametric speech synthesis , 2017, Speech Commun..

[15]  Liang Cai.  Research on Distributed Data Mining Technology based on K-mean Algorithm , 2017 .

[16]  Garrison W. Cottrell,et al.  A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction , 2017, IJCAI.

[17]  Ashfaqur Rahman,et al.  Recurrent Neural Networks for One Day Ahead Prediction of Stream Flow , 2016, TSAA '16.

[18]  Mirella Lapata,et al.  Long Short-Term Memory-Networks for Machine Reading , 2016, EMNLP.

[19]  Stephen G. Hall,et al.  ARIMA Models and the Box-Jenkins Methodology , 2016 .

[20]  Roger Frigola,et al.  Bayesian Time Series Learning with Gaussian Processes , 2015 .

[21]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[22]  Yoshua Bengio,et al.  Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.

[23]  Yoshua Bengio,et al.  Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.

[24]  Carlos Agón,et al.  Time-series data mining , 2012, CSUR.

[25]  Dong Zhou,et al.  Translation techniques in cross-language information retrieval , 2012, CSUR.

[26]  Tak-Chung Fu,et al.  A review on time series data mining , 2011, Eng. Appl. Artif. Intell..

[27]  Sergei Vassilvitskii,et al.  k-means++: the advantages of careful seeding , 2007, SODA '07.

[28]  T. Warren Liao,et al.  Clustering of time series data - a survey , 2005, Pattern Recognit..

[29]  Sariel Har-Peled,et al.  Smaller Coresets for k-Median and k-Means Clustering , 2005, SCG.

[30]  J. Elman.  Distributed Representations, Simple Recurrent Networks, And Grammatical Structure , 1991, Machine Learning.

[31]  Liu Zhen-tang,et al.  Principle of Predicting Coal and Gas Outburst Using Electromagnetic Emission , 2000 .

[32]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[33]  Gerald L. Morrison,et al.  Comparison of orifice and slotted plate flowmeters , 1994 .

[34]  P. Brockwell,et al.  Time Series: Theory and Methods , 2013 .

[35]  D. Dickey.  Time Series Theory and Methods , 1989 .

[36]  Peter Whittle,et al.  Hypothesis Testing in Time Series Analysis. , 1951 .