Open Journal of Applied Sciences

Open Journal of Applied Sciences

ISSN Print: 2165-3917
ISSN Online: 2165-3925
www.scirp.org/journal/ojapps
E-mail: ojapps@scirp.org
"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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[13] An Absolute Differences K-Means Clustering Approach on Determining Intervals to Optimize Fuzzy Time Series Markov Chain Model
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[14] Chaotic Logistic Map Forecast using Fuzzy Time Series
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[15] Improved Fuzzy Time Series Forecasting Model Based on Optimal Lengths of Intervals Using Hedge Algebras and Particle Swarm Optimization
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[16] A new hybrid fuzzy time series model with an application to predict PM10 concentration
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[17] Metode Peramalan Fuzzy Time Series–Markov Chain dengan Optimasi Interval Menggunakan Algoritma Fuzzy Subtractive Clustering (FSC)
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[18] METODE PERAMALAN FUZZY TIME SERIES-MARKOV CHAIN BERDASARKAN K-MEANS CLUSTERING
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[19] MÔ HÌNH DỰ BÁO CHUỖI THỜI GIAN MỜ DỰA TRÊN ĐẠI SỐ GIA TỬ VÀ TỐI ƯU BẦY ĐÀN
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[20] A Fuzzy Time Series Model Based on Improved Fuzzy Function and Cluster Analysis Problem
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[21] Markov Weighted Fuzzy Time-Series Model Based on an Optimum Partition Method for Forecasting Air Pollution
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[22] Interpolating time series based on fuzzy cluster analysis problem
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[23] A New Fuzzy Time Series Model Based on Cluster Analysis Problem
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[24] A NOVEL FORECASTING MODEL BASED ON COMBINING TIME-VARIANT FUZZY LOGICAL RELATIONSHIP GROUPS AND K-MEANS CLUSTERING TECHNIQUE
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[27] Handling Forecasting Problems Based on Two-Factor High-Order Fuzzy Time Series and Particle Swarm Optimization
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[29] Handling Forecasting Problems Based on Combining High-Order Time-Variant Fuzzy Relationship Groups and Particle Swam Optimization Technique
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[30] Fuzzy time series applications and extensions: analysis of a short term load forecasting challenge
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[31] Séries temporais fuzzy aplicadasa previsao de carga a curto prazo: aplicaçoes e extensoes
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[32] Improving the Forecasted Accuracy of Model Based on Fuzzy Time Series and K-Means Clustering
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[33] Forecasting Power Quality Events Using Advanced Fuzzy Time Series
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[34] Forecasting Simulation with ARIMA and Combination of Stevenson-Porter-Cheng Fuzzy Time Series
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[35] Data driven analysis using fuzzy time series for air quality management in Surabaya
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[36] A NOVEL FORECASTING MODEL BASED ON COMBINING TIME- VARIANT FUZZY LOGICAL RELATIONSHIP GROUPS AND K-MEANS CLUSTERING TECHNIQUE
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[37] • FORECASTING MODEL BASED ON FUZZY TIME SERIES WITH FIRST ORDER DIFFERENCING
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[39] Propositional architecture and the par-adox of prediction
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