Work

Forest fire pattern extraction and rule generation using sliding window technique

Year: 2009

Type: conference-paper

Abstract: The sliding window technique is being used to extract patterns of forest fire which consists of burnt area size, temperature, relative humidity, wind speed and rainfall.The initial data is being transformed by changing the continuous values of the attributes into categorical value. Extracted patterns are then being grouped based on the size of burnt are.Rules are then generated by transforming the categorical values into intervals and the merging different records into the same rules.The rule generation stage produces eight distinct patterns of meteorological conditions that could predict the size of forest fire.

Source: Universiti Utara Malaysia Institutional Repository (Universiti Utara Malaysia)

Authors: Ku Ruhana Ku‐Mahamud, Jia Yun Khor

Institution: Universiti Utara Malaysia

Language: English

Topic: Data Mining Algorithms and Applications

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W1518122856

FWCI:

Cites: 10

Cited by: 1

Related to: 10