Knowledge Resource Center for Ecological Environment in Arid Area
| 项目编号 | 61462058 |
| 针对多目标优化的人工蜂群算法改进及在水文模型参数优化中的应用 | |
| 火久元 | |
| 主持机构 | 兰州交通大学 |
| 开始日期 | 2015 |
| 结束日期 | 2018 |
| 资助经费 | 430000(CNY) |
| 项目类别 | 地区科学基金项目 |
| 资助机构 | CN-NSFC（国家自然科学基金） |
| 语种 | 中文 |
| 国家 | 中国 |
| 英文简介 | Given the current defects that existing in the multi-objective optimization algorithm, this study is to build optimization method that suitable for solving large-scale, multi-objective optimization problem. Aimed at multi-objective optimization problems in science and engineering practice, the study is to research and analyze the Artificial Bee Colony (ABC) algorithm and multi-objective optimization mechanism by using stochastic process theory, and put forward a more comprehensive system of multi-objective optimization theory based on ABC algorithm. Based on the theoretical system to establish a stable and efficient hybrid multi-objective ABC optimization algorithm and design a flexible, configurable multi-objective ABC optimization algorithm application framework that independent of the specific problems. In the high-performance computing environments, to propose a hydrological model parameter optimization method based the application framework and establish comprehensive evaluation mechanism of parameter optimization objects in Hydrological model. This method is to be applied to the SWAT, TOPMODEL Hydrological models in Heihe River Basin for validation and application of the aforementioned mechanisms, methods and techniques. The study can be more effective, more flexibility to deal with the actual large-scale multi-objective optimization problem, and has great significance for improving the system efficiency and promoting the reasonable utilization of resources. The application research in Heihe River Basin can significantly improve the simulation precision and parameter optimization convergence rate of Hydrological model, and provide important methods and techniques for hydrological model and water resources management decision in the arid inland river basin. |
| 来源机构 | 兰州交通大学 |
| 资源类型 | 项目 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/344344 |
| 推荐引用方式 GB/T 7714 | 火久元.针对多目标优化的人工蜂群算法改进及在水文模型参数优化中的应用.2015. |
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