Machine learning techniques in disease forecasting: A case study on rice blast prediction

BMC Bioinformatics

Volumn 7, Issue , 2006, Pages

  Kaundal, Rakesh ^a   Kapoor, Amar A ^b   Raghava, Gajendra P S ^a  

^a INSTITUTE OF MICROBIAL TECHNOLOGY   (India)

^b CSK HPAU ^*  (India)

Author keywords

[No Author keywords available]

Indexed keywords

AVERAGE CORRELATION COEFFICIENTS; BACK-PROPAGATION NEURAL NETWORKS; DECISION MAKING PROCESS; DISEASE FORECASTING; GENERALIZED REGRESSION NEURAL NETWORK(GRNN); MACHINE LEARNING TECHNIQUES; MULTIPLE REGRESSIONS; PREDICTOR VARIABLES;

AGRICULTURE; NEURAL NETWORKS; RESEARCH; SUPPORT VECTOR MACHINES;

FORECASTING;

ACCURACY; ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; CASE STUDY; CLIENT SERVER APPLICATION; CONTROLLED STUDY; CORRELATION COEFFICIENT; DATA ANALYSIS SOFTWARE; FORECASTING; INTERMETHOD COMPARISON; MULTIPLE REGRESSION; NONHUMAN; PLANT DISEASE; PREDICTION; RICE; SUPPORT VECTOR MACHINE; VALIDATION PROCESS; WEATHER; AGRICULTURE; ARTIFICIAL INTELLIGENCE; ASCOMYCETES; AUTOMATED PATTERN RECOGNITION; CLASSIFICATION; EVALUATION STUDY; MICROBIOLOGY; PATHOGENICITY; PROCEDURES;

AGRICULTURE; ARTIFICIAL INTELLIGENCE; ASCOMYCOTA; FORECASTING; PATTERN RECOGNITION, AUTOMATED; PLANT DISEASES; WEATHER;

EID: 33751287730     PISSN: 14712105     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-7-485     Document Type: Article

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