paper
2018
Local & station forecasting
New model or method
Classical ML (trees, GP, linear, kernels)6 h–3 days Journal
2018-10-30
004
Oct 2018
MALARKODI P, BARANIDHARAN N, ARUNACHALAM S
International Journal for Research in Science Engineering & Technology
ANFIS and multiple linear regression predict monthly station temperature, humidity, wind and pressure from 2008–2012 data; ANFIS gives lower RMSE.
Climatic Prognosticate Identification using Soft Computing Techniques and Algorithmic Concepts
In one sentence. ANFIS and multiple linear regression predict monthly station temperature, humidity, wind and pressure from 2008–2012 data; ANFIS gives lower RMSE.
Labels
- Topic
- Local & station forecasting
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 6 h–3 days
- Domain
- Local / station
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.5281/ijrset.v2i10.196 OpenAlex:W7215043424
- Added
- 2026-10-22
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