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Research And Design In Xinjiang Processing Tomatoes Group Decision Support System

Posted on:2015-02-26Degree:MasterType:Thesis
Country:ChinaCandidate:Z Q HanFull Text:PDF
GTID:2298330431492025Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
For balance of quality and quantity of processing tomato planting and processing,pest defense issue, tomato fruit quality cultivation and many other issues in Xinjiang,this study proposes "group" thinking which merges the advantages of Productionmanagement model and decision support methods. Tomato production managementinformation are widely collected and fully understood. Combined with the necessarysupport field trials, production forecasts, pest forecasting and quality evaluationmodel are constructed by control algorithms. In order to achieve the forecast,evaluation and management decision-making coupled with a comprehensive andcoordinated organic for the foundation for digital and modern processing tomatoproduction management decisions. The Processing Tomato Group Decision SupportSystem is preliminary designed through computer technology and component-basedprogramming principles.Research has made some progress, including:(1) Tomato yield LR-GM-IScombination forecasting model is established based on a combination of theoreticalpredictions and it improves the prediction accuracy compared with a single predictionmodel.(2) Elman neural network prediction model which describes the relationshipbetween tomato pests’ occurrence degree and meteorological factors has a goodprediction.(3)The study converts17agronomic traits into six comprehensiveevaluation and gives six main functional components by using principal componentanalysis.22tomato varieties are divided into three categories by Q-type clusteranalysis. Evaluation period is reduced to fertility, weight, lycopene, soluble solids,sugar-acid ratio by R-type cluster analysis.(4) Agronomic traits that associates degreewith mapping amount (soluble solids, lycopene, sugar-acid ratio, fruit resistance topressure) of special characters (high yield, good nutrition, good flavor, good storage)have been found by using gray correlation analysis of the target trait.(5)Three-tier architecture and the basic composition of function modules function modules ofPTGDSS system has been conducted a preliminary design. For systemimplementation, this study proposed specific considerations of principle...
Keywords/Search Tags:Processing tomato, Production Forecasts, Pest Forecasting, QualityEvaluation, Group Decision Support Systems
PDF Full Text Request
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