A variable precision rough set approach to knowledge discovery in land cover classification

International Journal of Digital Earth

Volumn 9, Issue 12, 2016, Pages 1206-1223

  Sikder, Iftikhar U ^a,b  

^a CLEVELAND STATE UNIVERSITY   (United States)

^b Cleveland State University   (United States)

Author keywords

approximate reasoning; granular computing; remote sensing; Rough set theory; soft computing

Indexed keywords

APPROXIMATION THEORY; CLASSIFICATION (OF INFORMATION); COMPUTATION THEORY; DECISION TREES; GRANULAR COMPUTING; LEARNING ALGORITHMS; REMOTE SENSING; SOFT COMPUTING; SUPPORT VECTOR MACHINES;

APPROXIMATE REASONING; LAND COVER CLASSIFICATION; PREDICTIVE PERFORMANCE; ROUGH-SET RULE INDUCTION; SPATIAL CLASSIFICATION; SUPERVISED CLASSIFICATION; SUPPORT VECTOR MACHINE METHOD; VARIABLE PRECISION ROUGH SETS;

ROUGH SET THEORY;

ALGORITHM; BAYESIAN ANALYSIS; LAND CLASSIFICATION; LAND COVER; MACHINE LEARNING; SUPPORT VECTOR MACHINE;

EID: 84976526025     PISSN: 17538947     EISSN: 17538955     Source Type: Journal    
DOI: 10.1080/17538947.2016.1194489     Document Type: Article

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