Responsive orbits have exhibited advantages in emergencies for their excellent responsiveness and coverage to targets.Generally,there are several conflicting metrics to trade in the orbit design for responsive space.A...Responsive orbits have exhibited advantages in emergencies for their excellent responsiveness and coverage to targets.Generally,there are several conflicting metrics to trade in the orbit design for responsive space.A special multiple-objective genetic algorithm,namely the Nondominated Sorting Genetic AlgorithmⅡ(NSGAⅡ),is used to design responsive orbits.This algorithm has considered the conflicting metrics of orbits to achieve the optimal solution,including the orbital elements and launch programs of responsive vehicles.Low-Earth fast access orbits and low-Earth repeat coverage orbits,two subtypes of responsive orbits,can be designed using NSGAI under given metric tradeoffs,number of vehicles,and launch mode.By selecting the optimal solution from the obtained Pareto fronts,a designer can process the metric tradeoffs conveniently in orbit design.Recurring to the flexibility of the algorithm,the NSGAI promotes the responsive orbit design further.展开更多
Focussing on unification of concrete portions into a generic form of computational evolution,a generalized theoretical framework is necessary and imperative to be built to construct a universal computational theory of...Focussing on unification of concrete portions into a generic form of computational evolution,a generalized theoretical framework is necessary and imperative to be built to construct a universal computational theory of evolution machine.The NP problem solving capacity can be traced to the nature of metaevolution mechanism with emergence features that determine corresponding homeostasis and diversity ranging in the domain of nonlinnear mapping from genotype to phenotype.In this paper a criterion that guarantees the global optimality of evolutionary computation process is proposed and proven rigorously.The global optimization criterion obtained is based on the nonparametric measarement for the whole evolution system and has great flexibility and evolvability.It leaves room for evolutionary system designing and developement.The formulization of the global description in statistical manifold space of information object family expresses evoluable evolutionary operator architecture and operation procedure in terms of evolution by evolution.The theoretical results are helpful to applications such as machine learning for automatic knowledge acquisition,pattern classification and recognition of complex images(e.q.OCR) and unsupervised system identification of nonlinear dynamical systems as well as chaos phenomena.The kernal of the formal system guided by global evolutionary optimization is proper to the implementation with objectoriented programming paradigm and abstract machine modelling.展开更多
文摘Responsive orbits have exhibited advantages in emergencies for their excellent responsiveness and coverage to targets.Generally,there are several conflicting metrics to trade in the orbit design for responsive space.A special multiple-objective genetic algorithm,namely the Nondominated Sorting Genetic AlgorithmⅡ(NSGAⅡ),is used to design responsive orbits.This algorithm has considered the conflicting metrics of orbits to achieve the optimal solution,including the orbital elements and launch programs of responsive vehicles.Low-Earth fast access orbits and low-Earth repeat coverage orbits,two subtypes of responsive orbits,can be designed using NSGAI under given metric tradeoffs,number of vehicles,and launch mode.By selecting the optimal solution from the obtained Pareto fronts,a designer can process the metric tradeoffs conveniently in orbit design.Recurring to the flexibility of the algorithm,the NSGAI promotes the responsive orbit design further.
文摘Focussing on unification of concrete portions into a generic form of computational evolution,a generalized theoretical framework is necessary and imperative to be built to construct a universal computational theory of evolution machine.The NP problem solving capacity can be traced to the nature of metaevolution mechanism with emergence features that determine corresponding homeostasis and diversity ranging in the domain of nonlinnear mapping from genotype to phenotype.In this paper a criterion that guarantees the global optimality of evolutionary computation process is proposed and proven rigorously.The global optimization criterion obtained is based on the nonparametric measarement for the whole evolution system and has great flexibility and evolvability.It leaves room for evolutionary system designing and developement.The formulization of the global description in statistical manifold space of information object family expresses evoluable evolutionary operator architecture and operation procedure in terms of evolution by evolution.The theoretical results are helpful to applications such as machine learning for automatic knowledge acquisition,pattern classification and recognition of complex images(e.q.OCR) and unsupervised system identification of nonlinear dynamical systems as well as chaos phenomena.The kernal of the formal system guided by global evolutionary optimization is proper to the implementation with objectoriented programming paradigm and abstract machine modelling.
基金国家自然科学基金(the National Natural Science Foundation of China under Grant No.60473012)国家科技公关计划项目(the KeyTechnologies R&D Program of China under Grant No.2003BA614A-14)+1 种基金江苏省自然科学基金(the Natural Science Foundation of JiangsuProvince of China under Grant No.BK2005047)南京大学软件新技术国家重点实验室开放基金。
