Urban natural resources comprise a complex system of water, land, forest, and air. They are the essential elements of sustainable economic and social development. However, few studies have been conducted on the dynami...
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Urban natural resources comprise a complex system of water, land, forest, and air. They are the essential elements of sustainable economic and social development. However, few studies have been conducted on the dynamic relationship between multi-resource ecosystem and natural resource ecological security. The present study aims to systematically examine the impact of water, land, forest, and air resource ecosystem on natural resource ecological security. First, this study establishes the ecological security evaluation system of natural resources based on the driving force-pressure-state-response model. Second, the study takes the Guangdong-Hong Kong-Macao Greater Bay Area as an example, and uses the wind-driven optimization algorithm to optimize the projection pursuit model to calculate the value of ecological security level. Then, it analyzes the spatial layout of regional natural resources ecological security, and discusses the influence mechanism of water, land, forest, and air resource subsystems on ecological security for natural resources. The study shows that the ecological security level of natural resources in nine cities in the Guangdong-Hong Kong-Macao Greater Bay Area increased as a whole from 2013 to 2018. However, the ecological security level in the central region of the Guangdong-Hong Kong-Macao Greater Bay Area is low, which is directly related to the severe environmental pollution of its water and air resources. The conclusions of this study are consistent with the reality and have high reliability. Therefore, this study can enrich the evaluation methods of ecological security and provide scientific guidance for improving urban natural resources and environment.
In this article, the atmospheric motion-based inspired wind-drivenoptimization (WDO) algorithm is implemented to minimize the traveling path length of a four-wheeled ground robot (FWGR) in different stationary and no...
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A sparse array synthesis method based on improved wind-driven optimization algorithm (IWDO) and fast Fourier transform (FFT) for the purpose of sidelobe suppression was introduced. First, the uniform linear array was ...
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A sparse array synthesis method based on improved wind-driven optimization algorithm (IWDO) and fast Fourier transform (FFT) for the purpose of sidelobe suppression was introduced. First, the uniform linear array was sparse by the FFT algorithm. Then the amplitude excitation weighting of array elements was optimized by IWDO algorithm based on probability factor chaotic map. During the optimization process, the minimum peak sidelobe level was used as the fitness function. By comparing with the simulation results of classic Chebyshev weighting method, the method proposed in this paper has better performance.
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