A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Multiobjective Optimization of Sensor Placement for Precipitation Station Monitoring Network Design
An optimal sensor placement of a precipitation station network should fulfill different regulations and requirements, such as coverage maximization, easy access, and uniform distribution. However, few studies have focused on an integrated way to optimize the precipitation network design from the perspective of monitoring efficiency in space. In this paper, given the complex requirements and diversified goals for precipitation monitoring, a new multiobjective location model is established for optimizing the network’s monitoring efficiency with a comprehensive weighting scheme. Based on the precipitation station siting regulations, the spatial coverage, accessibility, and dispersion of stations are considered in the model. The Elitist Nondominated Sorting Genetic Algorithm (NSGA-II) is used to obtain a set of Pareto-efficient solutions. The Jinsha River Basin is selected as the study region to test the proposed method. The results show that the proposed method satisfies the complex precipitation monitoring requirements and achieves higher coverage than the real-world deployment. The decision making for siting schemes, comparison of other dispersion models, and the extensibility of the proposed method are also discussed.
Multiobjective Optimization of Sensor Placement for Precipitation Station Monitoring Network Design
An optimal sensor placement of a precipitation station network should fulfill different regulations and requirements, such as coverage maximization, easy access, and uniform distribution. However, few studies have focused on an integrated way to optimize the precipitation network design from the perspective of monitoring efficiency in space. In this paper, given the complex requirements and diversified goals for precipitation monitoring, a new multiobjective location model is established for optimizing the network’s monitoring efficiency with a comprehensive weighting scheme. Based on the precipitation station siting regulations, the spatial coverage, accessibility, and dispersion of stations are considered in the model. The Elitist Nondominated Sorting Genetic Algorithm (NSGA-II) is used to obtain a set of Pareto-efficient solutions. The Jinsha River Basin is selected as the study region to test the proposed method. The results show that the proposed method satisfies the complex precipitation monitoring requirements and achieves higher coverage than the real-world deployment. The decision making for siting schemes, comparison of other dispersion models, and the extensibility of the proposed method are also discussed.
Multiobjective Optimization of Sensor Placement for Precipitation Station Monitoring Network Design
Wang, Ke (author) / Yang, Jia (author) / Peng, Yuling (author) / Wu, Qianqian (author) / Hu, Chuli (author)
2020-06-19
Article (Journal)
Electronic Resource
Unknown
A multiobjective evolutionary algorithm for surveillance sensor placement
| Online Contents | 2008
Actuator and Sensor Placement for Multiobjective Control of Structures
| British Library Online Contents | 1999
TECHNICAL PAPERS - Actuator and Sensor Placement for Multiobjective Control of Structures
| Online Contents | 1999
Multiobjective Contaminant Sensor Network Design for Water Distribution Systems
| British Library Online Contents | 2008