Geography requires a comprehensive understanding of both natural and human factors,as well as their interactions.Due to the complexity and multiplicity of geographic problems,various theories and methods for geographi...Geography requires a comprehensive understanding of both natural and human factors,as well as their interactions.Due to the complexity and multiplicity of geographic problems,various theories and methods for geographic modelling and simulation have been proposed.Currently,geography has entered an era in which quantitative analysis and modelling are essential for understanding the mechanisms of geographic processes.As the basic idea of quantitative spatial analysis,the specified space often needs to be partitioned by a series of small computational units(cells),i.e.,grids.Thus,there is a close relationship between the grids and geographic modelling.This article reviews the mainstream and typical grids used for modelling and simulation.In addition to classification,the derived theories and technologies,including grid generation methods,data organization strategies,multi-dimensional querying methods,and grid adaptation techniques,are discussed.For integrated geographic simulation to explore comprehensive geographic problems,we argued that it is reasonable to build bridges among different types of grids(e.g.,transformation strategies),and more powerful grids that can support multi-type of numerical computation are urgently needed.展开更多
Evolutionary computation （EC） is one of the fastest growing areas in computer science that solves intractable optimization problems by emulating biologic evolution and organizational behaviors in nature. To de- sign...Evolutionary computation （EC） is one of the fastest growing areas in computer science that solves intractable optimization problems by emulating biologic evolution and organizational behaviors in nature. To de- sign an EC algorithm, one needs to determine a set of algorithmic configurations like operator selections and parameter settings. How to design an effective and ef- ficient adaptation scheme for adjusting the configura- tions of EC algorithms has become a significant and promising research topic in the EC research community. This paper intends to provide a comprehensive survey on this rapidly growing field. We present a classification of adaptive EC （AEC） algorithms from the perspective of how an adaptation scheme is designed, involving the adaptation objects, adaptation evidences, and adapta- tion methods. In particular, by analyzing tile popula- tion distribution characteristics of EC algorithms, we discuss why and how the evolutionary state information of EC can be estimated and utilized for designing ef- fective EC adaptation schemes. Two AEC algorithms using the idea of evolutionary state estimation, includ- ing the clustering-based adaptive genetic algorithm and the adaptive particle swarm optimization algorithm are presented in detail. Some potential directions for the re- search of AECs are also discussed in this paper.展开更多
基金supported by the Excellent Young Scientists Fund(Grant No.41622108)the National Basic Research Program of China(973Program)(Grant No.2015CB954103)the Priority Academic Program Development of Jiangsu Higher Education Institutions(Grant No.164320H116)
文摘Geography requires a comprehensive understanding of both natural and human factors,as well as their interactions.Due to the complexity and multiplicity of geographic problems,various theories and methods for geographic modelling and simulation have been proposed.Currently,geography has entered an era in which quantitative analysis and modelling are essential for understanding the mechanisms of geographic processes.As the basic idea of quantitative spatial analysis,the specified space often needs to be partitioned by a series of small computational units(cells),i.e.,grids.Thus,there is a close relationship between the grids and geographic modelling.This article reviews the mainstream and typical grids used for modelling and simulation.In addition to classification,the derived theories and technologies,including grid generation methods,data organization strategies,multi-dimensional querying methods,and grid adaptation techniques,are discussed.For integrated geographic simulation to explore comprehensive geographic problems,we argued that it is reasonable to build bridges among different types of grids(e.g.,transformation strategies),and more powerful grids that can support multi-type of numerical computation are urgently needed.
文摘Evolutionary computation （EC） is one of the fastest growing areas in computer science that solves intractable optimization problems by emulating biologic evolution and organizational behaviors in nature. To de- sign an EC algorithm, one needs to determine a set of algorithmic configurations like operator selections and parameter settings. How to design an effective and ef- ficient adaptation scheme for adjusting the configura- tions of EC algorithms has become a significant and promising research topic in the EC research community. This paper intends to provide a comprehensive survey on this rapidly growing field. We present a classification of adaptive EC （AEC） algorithms from the perspective of how an adaptation scheme is designed, involving the adaptation objects, adaptation evidences, and adapta- tion methods. In particular, by analyzing tile popula- tion distribution characteristics of EC algorithms, we discuss why and how the evolutionary state information of EC can be estimated and utilized for designing ef- fective EC adaptation schemes. Two AEC algorithms using the idea of evolutionary state estimation, includ- ing the clustering-based adaptive genetic algorithm and the adaptive particle swarm optimization algorithm are presented in detail. Some potential directions for the re- search of AECs are also discussed in this paper.
