[Objective] This paper aims to construct an improved fuzzy decision tree which is based on clustering,and researches into its application in the screening of maize germplasm.[Method] A new decision tree algorithm base...[Objective] This paper aims to construct an improved fuzzy decision tree which is based on clustering,and researches into its application in the screening of maize germplasm.[Method] A new decision tree algorithm based upon clustering is adopted in this paper,which is improved against the defect that traditional decision tree algorithm fails to handle samples of no classes.Meanwhile,the improved algorithm is also applied to the screening of maize varieties.Through the indices as leaf area,plant height,dry weight,potassium（K） utilization and others,maize seeds with strong tolerance of hypokalemic are filtered out.[Result] The algorithm in the screening of maize germplasm has great applicability and good performance.[Conclusion] In the future more efforts should be made to compare improved the performance of fuzzy decision tree based upon clustering with the performance of traditional fuzzy one,and it should be applied into more realistic problems.展开更多
To screen out the rapeseed(Brassica napus) combinations that are suitable for the production of both oilseed and vegetable, we carried out a field experiment for 11 new combinations(hybrids) of rapeseed and then perfo...To screen out the rapeseed(Brassica napus) combinations that are suitable for the production of both oilseed and vegetable, we carried out a field experiment for 11 new combinations(hybrids) of rapeseed and then performed grey relation analysis and cluster analysis on 12 traits including the yield and quality of young stem,seed yield, and several agronomic traits after harvesting of young stem. The results showed that A11, A7, and A4 had higher main stalk yield than other combinations.The young stem/leaf ratios of A11, A5, A7, A4, A3, and A1 were in line with the quality requirements for young stem commodity. The soluble sugar content of A2,A8, and A10 was higher than that of CK(Fengyou 737), and the seed yields of A4,A3, A2, A1, A5, and A6 were higher than that of CK. The 11 rapeseed combinations were classified into 3 grades by grey relation analysis and cluster analysis. Two combinations, A4(Y20A×95C4R) and A11(3194A×09-5R), showed the weighted relation degrees higher than 0.95, which were clustered into grade I by cluster analysis. They had good agronomic traits and good performance as both oilseed and vegetable. A8, A5, A3, A7, A2, A10, A6, and A1 were clustered into grade Ⅱ and A9 into grade Ⅲ. In this study, the oilseed and vegetable dual-purpose rapeseed combinations were screened out based on grey relation analysis and cluster analysis,which can provide reference for the breeding of oilseed and vegetable dual-purpose rapeseed combinations.展开更多
文摘[Objective] This paper aims to construct an improved fuzzy decision tree which is based on clustering,and researches into its application in the screening of maize germplasm.[Method] A new decision tree algorithm based upon clustering is adopted in this paper,which is improved against the defect that traditional decision tree algorithm fails to handle samples of no classes.Meanwhile,the improved algorithm is also applied to the screening of maize varieties.Through the indices as leaf area,plant height,dry weight,potassium（K） utilization and others,maize seeds with strong tolerance of hypokalemic are filtered out.[Result] The algorithm in the screening of maize germplasm has great applicability and good performance.[Conclusion] In the future more efforts should be made to compare improved the performance of fuzzy decision tree based upon clustering with the performance of traditional fuzzy one,and it should be applied into more realistic problems.
文摘To screen out the rapeseed(Brassica napus) combinations that are suitable for the production of both oilseed and vegetable, we carried out a field experiment for 11 new combinations(hybrids) of rapeseed and then performed grey relation analysis and cluster analysis on 12 traits including the yield and quality of young stem,seed yield, and several agronomic traits after harvesting of young stem. The results showed that A11, A7, and A4 had higher main stalk yield than other combinations.The young stem/leaf ratios of A11, A5, A7, A4, A3, and A1 were in line with the quality requirements for young stem commodity. The soluble sugar content of A2,A8, and A10 was higher than that of CK(Fengyou 737), and the seed yields of A4,A3, A2, A1, A5, and A6 were higher than that of CK. The 11 rapeseed combinations were classified into 3 grades by grey relation analysis and cluster analysis. Two combinations, A4(Y20A×95C4R) and A11(3194A×09-5R), showed the weighted relation degrees higher than 0.95, which were clustered into grade I by cluster analysis. They had good agronomic traits and good performance as both oilseed and vegetable. A8, A5, A3, A7, A2, A10, A6, and A1 were clustered into grade Ⅱ and A9 into grade Ⅲ. In this study, the oilseed and vegetable dual-purpose rapeseed combinations were screened out based on grey relation analysis and cluster analysis,which can provide reference for the breeding of oilseed and vegetable dual-purpose rapeseed combinations.
