Increasing numbers of approaches to assess eutrophication, such as estuarine trophic status, the Oslo-Paris Commission Common Procedure, and the Water Framework Directive, focus on the symptoms of eutrophication. In C...Increasing numbers of approaches to assess eutrophication, such as estuarine trophic status, the Oslo-Paris Commission Common Procedure, and the Water Framework Directive, focus on the symptoms of eutrophication. In China, however, nutrient index methods dominate the assessment of coastal waters. In this study, an integrated method that includes both water quality and ecological response was compared with the Northwest Pacifi c Action Plan (NOWPAP) Common Procedure. Observation data from Jiaozhou Bay, Shandong, China, were used in a comparison of the two methods in a trophic status study. Overall, both clearly revealed a high level of nutrient enrichment in the bay, indicated by high nutrient concentrations. Though the two methods diff ered in their methodological design in the assessment of the ecological eff ects of nutrient enrichment, they have acquired similar results: the integrated method suggested that the status was good, and the NOWPAP Common Procedure suggested that the status was low (indicating that the bay had no serious eutrophication problem). The introduction of fi lter feeders (shellfi sh aquaculture) into the bay on a reasonable scale may have been eff ective in mitigating eutrophic conditions, and perhaps explains the low ecological impacts there. Our results will be useful to ecosystem-based eutrophication management in the bay and in similar areas.展开更多
The approaches to discrete approximation of Pareto front using multi-objective evolutionary algorithms have the problems of heavy computation burden, long running time and missing Pareto optimal points. In order to ov...The approaches to discrete approximation of Pareto front using multi-objective evolutionary algorithms have the problems of heavy computation burden, long running time and missing Pareto optimal points. In order to overcome these problems, an approach to continuous approximation of Pareto front using geometric support vector regression is presented. The regression model of the small size approximate discrete Pareto front is constructed by geometric support vector regression modeling and is described as the approximate continuous Pareto front. In the process of geometric support vector regression modeling, considering the distribution characteristic of Pareto optimal points, the separable augmented training sample sets are constructed by shifting original training sample points along multiple coordinated axes. Besides, an interactive decision-making(DM)procedure, in which the continuous approximation of Pareto front and decision-making is performed interactively, is designed for improving the accuracy of the preferred Pareto optimal point. The correctness of the continuous approximation of Pareto front is demonstrated with a typical multi-objective optimization problem. In addition,combined with the interactive decision-making procedure, the continuous approximation of Pareto front is applied in the multi-objective optimization for an industrial fed-batch yeast fermentation process. The experimental results show that the generated approximate continuous Pareto front has good accuracy and completeness. Compared with the multi-objective evolutionary algorithm with large size population, a more accurate preferred Pareto optimal point can be obtained from the approximate continuous Pareto front with less computation and shorter running time. The operation strategy corresponding to the final preferred Pareto optimal point generated by the interactive DM procedure can improve the production indexes of the fermentation process effectively.展开更多
The core of the nonparametric/semiparametric Bayesian analysis is to relax the particular parametric assumptions on the distributions of interest to be unknown and random,and assign them a prior.Selecting a suitable p...The core of the nonparametric/semiparametric Bayesian analysis is to relax the particular parametric assumptions on the distributions of interest to be unknown and random,and assign them a prior.Selecting a suitable prior therefore is especially critical in the nonparametric Bayesian fitting.As the distribution of distribution,Dirichlet process(DP)is the most appreciated nonparametric prior due to its nice theoretical proprieties,modeling flexibility and computational feasibility.In this paper,we review and summarize some developments of DP during the past decades.Our focus is mainly concentrated upon its theoretical properties,various extensions,statistical modeling and applications to the latent variable models.展开更多
基金Supported by the National Key Research and Development Program of China(No.2016YFE0101500)the Aoshan Talents Cultivation Program(No.2017ASTCP-OS16)+1 种基金the National Key Research and Development Program of China(No.2017YFC1404306)the NSFC-Shandong Joint Fund for the Marine Science Research Center(No.U1606404)
文摘Increasing numbers of approaches to assess eutrophication, such as estuarine trophic status, the Oslo-Paris Commission Common Procedure, and the Water Framework Directive, focus on the symptoms of eutrophication. In China, however, nutrient index methods dominate the assessment of coastal waters. In this study, an integrated method that includes both water quality and ecological response was compared with the Northwest Pacifi c Action Plan (NOWPAP) Common Procedure. Observation data from Jiaozhou Bay, Shandong, China, were used in a comparison of the two methods in a trophic status study. Overall, both clearly revealed a high level of nutrient enrichment in the bay, indicated by high nutrient concentrations. Though the two methods diff ered in their methodological design in the assessment of the ecological eff ects of nutrient enrichment, they have acquired similar results: the integrated method suggested that the status was good, and the NOWPAP Common Procedure suggested that the status was low (indicating that the bay had no serious eutrophication problem). The introduction of fi lter feeders (shellfi sh aquaculture) into the bay on a reasonable scale may have been eff ective in mitigating eutrophic conditions, and perhaps explains the low ecological impacts there. Our results will be useful to ecosystem-based eutrophication management in the bay and in similar areas.
基金Supported by the National Natural Science Foundation of China(20676013,61240047)
文摘The approaches to discrete approximation of Pareto front using multi-objective evolutionary algorithms have the problems of heavy computation burden, long running time and missing Pareto optimal points. In order to overcome these problems, an approach to continuous approximation of Pareto front using geometric support vector regression is presented. The regression model of the small size approximate discrete Pareto front is constructed by geometric support vector regression modeling and is described as the approximate continuous Pareto front. In the process of geometric support vector regression modeling, considering the distribution characteristic of Pareto optimal points, the separable augmented training sample sets are constructed by shifting original training sample points along multiple coordinated axes. Besides, an interactive decision-making(DM)procedure, in which the continuous approximation of Pareto front and decision-making is performed interactively, is designed for improving the accuracy of the preferred Pareto optimal point. The correctness of the continuous approximation of Pareto front is demonstrated with a typical multi-objective optimization problem. In addition,combined with the interactive decision-making procedure, the continuous approximation of Pareto front is applied in the multi-objective optimization for an industrial fed-batch yeast fermentation process. The experimental results show that the generated approximate continuous Pareto front has good accuracy and completeness. Compared with the multi-objective evolutionary algorithm with large size population, a more accurate preferred Pareto optimal point can be obtained from the approximate continuous Pareto front with less computation and shorter running time. The operation strategy corresponding to the final preferred Pareto optimal point generated by the interactive DM procedure can improve the production indexes of the fermentation process effectively.
基金supported in part by the National Natural Science Foundation of China(Grant No.11471161)the Technological Innovation Item in Jiangsu Province(No.BK2008156).
文摘The core of the nonparametric/semiparametric Bayesian analysis is to relax the particular parametric assumptions on the distributions of interest to be unknown and random,and assign them a prior.Selecting a suitable prior therefore is especially critical in the nonparametric Bayesian fitting.As the distribution of distribution,Dirichlet process(DP)is the most appreciated nonparametric prior due to its nice theoretical proprieties,modeling flexibility and computational feasibility.In this paper,we review and summarize some developments of DP during the past decades.Our focus is mainly concentrated upon its theoretical properties,various extensions,statistical modeling and applications to the latent variable models.
