An improved moth flame optimization algorithm based on rough sets for tomato diseases detection

•Feature selection algorithm using the integration of moths-flame optimization and rough set was introduced.•Automatic tomato disease detection approach based on moths-flame optimization and rough set was proposed.•Dataset of tomato leaves infected with disease was collected.•The results demonstrate...

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Veröffentlicht in:	Computers and electronics in agriculture Jg. 136; S. 86 - 96
Hauptverfasser:	Hassanien, Aboul Ella, Gaber, Tarek, Mokhtar, Usama, Hefny, Hesham
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 15.04.2017 Elsevier BV
Schlagworte:	Agronomy automatic detection Blight Butterflies & moths data collection disease detection Fitness Fungi Genetic algorithms Machine learning Moth flame optimization Optimization Particle swarm optimization Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) Plant diseases powdery mildew Rough set theory Size reduction Solanum lycopersicum var. lycopersicum Support vector machines Theory tomatoes Tomato’s disease Rough set theory Moth flame optimization Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) Tomato’s disease
ISSN:	0168-1699, 1872-7107
Online-Zugang:	Volltext
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