[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 better understand different users' accessing intentions, a novel clustering and supervising method based on accessing path is presented. This method divides users' interest space to express the distribution...To better understand different users' accessing intentions, a novel clustering and supervising method based on accessing path is presented. This method divides users' interest space to express the distribution of users' interests, and directly to instruct the constructing process of web pages indexing for advanced performance.展开更多
[Objectives]The most common gene fragment used in animal DNA barcode technology is COI,but it is not necessarily suitable for all species.This study was conducted to screen genes suitable for the DNA barcode of sea sn...[Objectives]The most common gene fragment used in animal DNA barcode technology is COI,but it is not necessarily suitable for all species.This study was conducted to screen genes suitable for the DNA barcode of sea snakes.[Methods]All COI and cytb gene sequences on GenBank were searched and downloaded.After the comparison with Mega software,clustering trees of MrBayes system were established.[Results]Interspecies distances were greater than intraspecies distances for the two genes.The topological structures of their molecular hierarchical clustering trees were clear,and the support rates were high.[Conclusions]Therefore,it is concluded that not the DNA barcode of each species must be gene COI.Cytb is more suitable in terms of the mitochondrial gene of sea snakes.展开更多
Birch(Betula tortuosa)is one of the treeline forming species within the Siberian Mountains.We analysed the area dynamics of birch stands and the upslope climb of birch treeline based on the Landsat time series scenes ...Birch(Betula tortuosa)is one of the treeline forming species within the Siberian Mountains.We analysed the area dynamics of birch stands and the upslope climb of birch treeline based on the Landsat time series scenes and on-ground data.We found that since the warming onset(1970th)birch area increased by 10%,birch stands and treeline boundary were moving upslope with a rate of 1.4 m/yr and 4.0 m/yr.Birch upslope shift correlated with air temperatures at the beginning(May-June)and the end(August-October)of the growth period.Meanwhile,no correlation was found between birch upslope migration and precipitation.Winds negatively influenced both birch area growth and birch upslope climb during spring,fall,and wintertime.In the windy habitats,birch,together with larch and Siberian pine,formed clusters(hedges)which mitigated the influence of adverse winds.These clusters are the adaptive pattern for trees’upslope climb within windward slopes.The other adaptation to the harsh alpine ecotone habitat is non-leaf(bark)photosynthesis which supports tree survival.Thereby,Betula tortuosa upslope climb depends on the wind impact and warming in spring and fall that extended growth period.With ongoing warming and observed wind speed decrease on the background of sufficient precipitation,it is expected to further birch advance into alpine tundra in the Siberian Mountains.展开更多
To address the problems that input variables should be reduced as much as possible and explain output variables fully in building neural network model of complicated system, a variable selection method based on cluste...To address the problems that input variables should be reduced as much as possible and explain output variables fully in building neural network model of complicated system, a variable selection method based on cluster (analysis) was investigated. Similarity coefficient which describes the mutual relation of variables was defined. The methods of the highest contribution rate, part replacing whole and variable replacement are put forwarded and deduced by information theory. The software of the neural network based on cluster analysis, which can provide many kinds of methods for defining variable similarity coefficient, clustering system variable and evaluating variable cluster, was developed and applied to build neural network forecast model of cement clinker quality. The results show that all the network scale, training time and prediction accuracy are perfect. The practical application demonstrates that the method of selecting variables for neural network is feasible and effective.展开更多
A checkpointing scheme for relevant distributed real-time tasks which can be scheduled as a DAG is proposed. A typical algorithm, OSA, is selected for DAG scheduling. A new methods based a new structure, Scheduled Clu...A checkpointing scheme for relevant distributed real-time tasks which can be scheduled as a DAG is proposed. A typical algorithm, OSA, is selected for DAG scheduling. A new methods based a new structure, Scheduled Cluster Tree, is presented to calculate the slack time of each task in the task cluster. In the checkpointing scheme, the optimal checkpoint intervals which minimize the approximated failure probability are derived formally and validated experimentally. The complexity of approximated failure probability is quite small compared with that of the exact probability. Meanwhile, the consistency of the checkpointing is discussed also.展开更多
The probability of default(PD) is the key element in the New Basel Capital Accord and the most essential factor to financial institutions' risk management.To obtain good PD estimation,practitioners and academics h...The probability of default(PD) is the key element in the New Basel Capital Accord and the most essential factor to financial institutions' risk management.To obtain good PD estimation,practitioners and academics have put forward numerous default prediction models.However,how to use multiple models to enhance overall performance on default prediction remains untouched.In this paper,a parametric and non-parametric combination model is proposed.Firstly,binary logistic regression model(BLRM),support vector machine(SVM),and decision tree(DT) are used respectively to establish models with relatively stable and high performance.Secondly,in order to make further improvement to the overall performance,a combination model using the method of multiple discriminant analysis(MDA) is constructed.In this way,the coverage rate of the combination model is greatly improved,and the risk of miscarriage is effectively reduced.Lastly,the results of the combination model are analyzed by using the K-means clustering,and the clustering distribution is consistent with a normal distribution.The results show that the combination model based on parametric and non-parametric can effectively enhance the overall performance on default prediction.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 better understand different users' accessing intentions, a novel clustering and supervising method based on accessing path is presented. This method divides users' interest space to express the distribution of users' interests, and directly to instruct the constructing process of web pages indexing for advanced performance.
基金Supported by Hainan Provincial Natural Science Foundation of China,High-level Talent Project(321RC587),Classification of sea snakes in the South Sea China based on molecular Systematics,morphology and climate modelSpecial Scientific Research Trial Production Project of Sanya City(2016KS05),Identification of sea snake species and construction of DNA barcoding based on molecular systematics.
文摘[Objectives]The most common gene fragment used in animal DNA barcode technology is COI,but it is not necessarily suitable for all species.This study was conducted to screen genes suitable for the DNA barcode of sea snakes.[Methods]All COI and cytb gene sequences on GenBank were searched and downloaded.After the comparison with Mega software,clustering trees of MrBayes system were established.[Results]Interspecies distances were greater than intraspecies distances for the two genes.The topological structures of their molecular hierarchical clustering trees were clear,and the support rates were high.[Conclusions]Therefore,it is concluded that not the DNA barcode of each species must be gene COI.Cytb is more suitable in terms of the mitochondrial gene of sea snakes.
基金The research was funded by Russian Foundation for Basic Research,Krasnoyarsk Territory and Krasnoyarsk Regional Fund of Science,project number 20-44-240007.
文摘Birch(Betula tortuosa)is one of the treeline forming species within the Siberian Mountains.We analysed the area dynamics of birch stands and the upslope climb of birch treeline based on the Landsat time series scenes and on-ground data.We found that since the warming onset(1970th)birch area increased by 10%,birch stands and treeline boundary were moving upslope with a rate of 1.4 m/yr and 4.0 m/yr.Birch upslope shift correlated with air temperatures at the beginning(May-June)and the end(August-October)of the growth period.Meanwhile,no correlation was found between birch upslope migration and precipitation.Winds negatively influenced both birch area growth and birch upslope climb during spring,fall,and wintertime.In the windy habitats,birch,together with larch and Siberian pine,formed clusters(hedges)which mitigated the influence of adverse winds.These clusters are the adaptive pattern for trees’upslope climb within windward slopes.The other adaptation to the harsh alpine ecotone habitat is non-leaf(bark)photosynthesis which supports tree survival.Thereby,Betula tortuosa upslope climb depends on the wind impact and warming in spring and fall that extended growth period.With ongoing warming and observed wind speed decrease on the background of sufficient precipitation,it is expected to further birch advance into alpine tundra in the Siberian Mountains.
文摘To address the problems that input variables should be reduced as much as possible and explain output variables fully in building neural network model of complicated system, a variable selection method based on cluster (analysis) was investigated. Similarity coefficient which describes the mutual relation of variables was defined. The methods of the highest contribution rate, part replacing whole and variable replacement are put forwarded and deduced by information theory. The software of the neural network based on cluster analysis, which can provide many kinds of methods for defining variable similarity coefficient, clustering system variable and evaluating variable cluster, was developed and applied to build neural network forecast model of cement clinker quality. The results show that all the network scale, training time and prediction accuracy are perfect. The practical application demonstrates that the method of selecting variables for neural network is feasible and effective.
文摘A checkpointing scheme for relevant distributed real-time tasks which can be scheduled as a DAG is proposed. A typical algorithm, OSA, is selected for DAG scheduling. A new methods based a new structure, Scheduled Cluster Tree, is presented to calculate the slack time of each task in the task cluster. In the checkpointing scheme, the optimal checkpoint intervals which minimize the approximated failure probability are derived formally and validated experimentally. The complexity of approximated failure probability is quite small compared with that of the exact probability. Meanwhile, the consistency of the checkpointing is discussed also.
基金supported by the National Natural Science Foundation of China Key Project under Grant No.70933003the National Natural Science Foundation of China under Grant Nos.70871109 and 71203247
文摘The probability of default(PD) is the key element in the New Basel Capital Accord and the most essential factor to financial institutions' risk management.To obtain good PD estimation,practitioners and academics have put forward numerous default prediction models.However,how to use multiple models to enhance overall performance on default prediction remains untouched.In this paper,a parametric and non-parametric combination model is proposed.Firstly,binary logistic regression model(BLRM),support vector machine(SVM),and decision tree(DT) are used respectively to establish models with relatively stable and high performance.Secondly,in order to make further improvement to the overall performance,a combination model using the method of multiple discriminant analysis(MDA) is constructed.In this way,the coverage rate of the combination model is greatly improved,and the risk of miscarriage is effectively reduced.Lastly,the results of the combination model are analyzed by using the K-means clustering,and the clustering distribution is consistent with a normal distribution.The results show that the combination model based on parametric and non-parametric can effectively enhance the overall performance on default prediction.
