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首页> 外文会议>IEEE International Conference on Information Systems and Computer Aided Education >Analysis of Site Selection Optimization of Construction Industrialization Base via Improved Particle Swarm Optimization Algorithm
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Analysis of Site Selection Optimization of Construction Industrialization Base via Improved Particle Swarm Optimization Algorithm

机译：基于改进粒子群算法的建筑工业化基地选址优化分析

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In order to select the site of the construction industrialization base scientifically and rationally, the METROPOLIS sampling and membrane computing methods are adopted to improve the particle swarm optimization algorithm, and the realization of the improved algorithm in the optimization of the site selection of the construction industrialization base is introduced. In this study, the quantity of the construction base is determined in the actual terrain, and the optimization results before and after the improvement of particle swarm optimization algorithm are compared and analyzed. The result shows that the terrain here is suitable for the establishment of 7 construction industrialization bases. In the optimization of site selection, the improved particle swarm optimization algorithm can help to obtain better site selection optimization results, whose fitness is improved from 1.75 to nearly 1.87. It proves that the improved particle swarm optimization algorithm via METROPOLIS sampling and membrane computing is more efficient than the traditional one. This study is of very important reference value for the application of improved particle swarm optimization in construction industrialization.
机译：为了科学合理地选择建筑工业化基地，采用METROPOLIS采样和膜计算方法对粒子群优化算法进行改进，并在改进建筑工业化选址中实现改进算法。基础介绍。本研究在实际地形中确定了施工基地的数量，并对改进粒子群算法前后的优化结果进行了比较和分析。结果表明，这里的地形适合建立7个建筑产业化基地。在选址优化中，改进的粒子群优化算法可以帮助获得更好的选址优化结果，其适用度从1.75提高到近1.87。实践证明，通过METROPOLIS采样和膜计算的改进粒子群优化算法比传统算法更有效。该研究对于改进粒子群算法在建筑工业化中的应用具有非常重要的参考价值。

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