Alternative method: outlier treatments with box-jenkins and neural network via interpolation method
Outliers represent the points that greatly diverge and act differently from the rest of the points. These kinds of phenomenon usually happen in the data especially in time series data. The presence of this outlier gave bad effect in all statistical method including forecasting if there are no action...
Saved in:
Main Authors: | Wahir, Norsoraya Azurin, Nor, Maria Elena, Rusiman, Mohd Saifullah, Pillay, Khuneswari Gopal |
---|---|
Format: | Article |
Language: | English |
Published: |
UTHM Publisher
2018
|
Subjects: | |
Online Access: | http://eprints.uthm.edu.my/5971/1/AJ%202017%20%28924%29.pdf http://eprints.uthm.edu.my/5971/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Alternative method outlier treatments with Box-Jenkins and neural network via interpolation method
by: Wahir, Norsoraya Azurin, et al.
Published: (2018) -
Multi-convolution feature extraction and recurrent neural network dependent model for short-term load forecasting
by: Goh, Hui Hwang, et al.
Published: (2021) -
Minimizing information asymmetry interference using optimal channel assignment strategy in wireless mesh networks
by: Rahman, Gohar, et al.
Published: (2019) -
Network monitoring system to detect unauthorized connection
by: A Hamid, Isredza Rahmi, et al.
Published: (2017) -
Daylight adaptive optimal lighting system control strategies for energy savings and visual comfort in commercial buildings
by: Wagiman, Khairul Rijal
Published: (2020)