A fuzzy seasonal ARIMA model for forecasting

By Fang-Mei Tseng, Gwo-Hshiung Tzeng. 2002

183 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research, Statistics and Probability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yao Dong
2. Jianzhou Wang
3. Ge Zhao
4. Yuanyuan Wang

In Management Science and Operations Research

1. Yao Dong
2. Jianzhou Wang
3. Ge Zhao
4. Yuanyuan Wang

In Statistics and Probability

1. Yao Dong
2. Jianzhou Wang
3. Ge Zhao
4. Yuanyuan Wang

Citations in the corpus

• Application of residual modification approach in seasonal ARIMA for electricity demand forecasting: A case study of China (2012, methodology): “In addition, four-step iterative cycles are needed to fit an S-ARIMA model (Tseng and Tzeng, 2002; Chen and Wang, 2007) as follows: (1) Identify the structure of the S-ARIMA(p, d, q)(P, D, Q)S model; (2) Estimate unknown parameters; (3) Perform goodness-of-fit tests on the estimated residuals; (4)…”