Optimization and Decision-Making in Relation to Rainfall for Crop Management Techniques

摘要: Disease prediction has a high degree of uncertainty which is due to the complex and imperfect nature symptoms that are used in diagnosis. Diseases continue be threat crop yield investments even though technological advancements have been made agricultural sector. Clinically screened database taken as knowledge base for weather symptoms. The present work highlights effect different parameters on rainfall then further utilizes findings decision-making production including disease detection selection. Parameters this experiment Wind Speed (WS), Relative Humidity (RH) Temperature (T). Taguchi Orthogonal arrays (OA) will data optimization. Parameter optimization done with help ANOVA (Analysis Variance).