Double layer domain guided intelligent optimizing configuration method of rural resident areas

Abstract

The invention discloses a double-layer domain-oriented intelligent optimal configuration method for rural residential areas. The intelligent optimal configuration method for rural residential areas provided by the invention firstly uses a radiation model to construct a village-town connection network, and generates a village-town weighted Voronoi diagram based on the evaluation of village-town network characteristics. , to identify the central village (town) domain and grass-roots village domain in the spatial planning of the village and town system, and to construct a dual-domain-oriented rural The particle swarm optimization model of residential areas, through the parallel search of particles in the two-layer domain space of villages and towns and the solution of optimization problems, generates an optimal configuration plan for rural residential areas. The invention solves the technical problems of insufficient spatial orientation and difficult coordination of multi-objectives in current rural residential planning, and improves the scientificity and rationality of rural residential planning.

Description

technical field [0001] The invention relates to a double-layer domain-oriented intelligent optimization configuration method for rural residential areas, which integrates a weighted Voronoi diagram and a particle swarm intelligent optimization algorithm to realize optimal spatial allocation of rural residential areas, and belongs to the field of land use planning. Background technique [0002] The optimal allocation of rural residential areas is an important part of promoting new urbanization, reconstructing rural space and rationally utilizing land resources, and is the core issue of rural land use. It is subject to multiple constraints and influences of regional nature, society, and economy, and involves multi-objective collaborative optimization of land type, quantity, and space. It is a complex nonlinear composite geographic process. With the increase of site selection space and the number of rural residential areas, the amount of spatial information has risen sharply, a...

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Problems solved by technology

Traditional modeling methods rely heavily on empirical knowledge, and it is difficult to solve nonlinear and multi-objective constraints in the optimal allocation of land use space; dynamic spatial models based on complex system theory and swarm intelligence optimization algorithms provide a new solution to such problems. ideas, including geographic simulation systems represented by cellular aut...

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