Data · dataset · 2016
A clustering based forecasting algorithm for multivariable fuzzy time series using linear combinations of independent variables
Listed in Teesside University Research Data Repository
Dear Researcher, Thank you for using this code and datasets.
Description
I explain how CFTS code related to my paper "A clustering based forecasting algorithm for multivariable fuzzy time series using linear combinations of independent variables" published in Applied Soft Computing works. All datasets mentioned in the paper accompanied with CFTS code are included.
If there is any question feel free to contact me at: bas_salaraskari@yahoo.com s_askari@aut.ac.ir Regards, S. Askari Guidelines for CFTS algorithm: 1. Open the file CFTS Code using MATLAB. 2. Enter or paste name of the dataset you wish to simulate in line 5 after "load".
Read the rest (3 more)
It loads the dataset in the workplace. 3. Lines 6 and 7: "r" is number of independent variables and "N" is number of data vectors used for training. 4. Line 9: "C" is number of clusters.
You can use the optimal number of clusters given in Table 6 of paper or your own preferred value. 5. If line 28 is "comment", covariance norm (Mahalanobis distance) is use and if it is "uncomment", identity norm (Euclidean distance) is used. 6. Please press Ctrl Enter to run the code. 7.
For your own dataset, please arrange the data as the datasets described in MS Word file "Read Me".
Links
Where it is published
- DOI doi.org/10.17632/35fw8pb6s9.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science
- Inferred from text
- Tabular 65%
Provenance · 1 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/35fw8pb6s9.1 | 9 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:tabular | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |