"Fuzzy Time Series Forecasting Based On K-Means Clustering"
written by Zhiqiang Zhang, Qiong Zhu,
published by Open Journal of Applied Sciences, Vol.2 No.4B, 2012
has been cited by the following article(s):
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[1] A New Fuzzy Time Series Model Based on Cluster Analysis Problem
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[2] A NOVEL FORECASTING MODEL BASED ON COMBINING TIME-VARIANT FUZZY LOGICAL RELATIONSHIP GROUPS AND K-MEANS CLUSTERING TECHNIQUE
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[3] (1906-5269) Interpolating time series based on fuzzy cluster analysis problem
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[4] Handling Forecasting Problems Based on Two-Factor High-Order Fuzzy Time Series and Particle Swarm Optimization
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[5] Handling Forecasting Problems Based on Combining High-Order Time-Variant Fuzzy Relationship Groups and Particle Swam Optimization Technique
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[6] Fuzzy time series applications and extensions: analysis of a short term load forecasting challenge
ITISE Conference, 2018
[7] Séries temporais fuzzy aplicadasa previsao de carga a curto prazo: aplicaçoes e extensoes
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[8] Improving the Forecasted Accuracy of Model Based on Fuzzy Time Series and K-Means Clustering
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[9] Forecasting Power Quality Events Using Advanced Fuzzy Time Series
2017
[10] Forecasting Simulation with ARIMA and Combination of Stevenson-Porter-Cheng Fuzzy Time Series
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[11] Data driven analysis using fuzzy time series for air quality management in Surabaya
2017
[12] • FORECASTING MODEL BASED ON FUZZY TIME SERIES WITH FIRST ORDER DIFFERENCING
2016
[13] 基於不同連結策略之集群式預測模式於伺服器銷售預測
臺灣健行科技大學學位論文, 2015
[14] Propositional architecture and the par-adox of prediction
archi-DOCT, 2015