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加权全局人工蜂群算法提高气体传感器部署效率。

Weighted Global Artificial Bee Colony Algorithm Makes Gas Sensor Deployment Efficient.

作者信息

Jiang Ye, He Ziqing, Li Yanhai, Xu Zhengyi, Wei Jianming

机构信息

Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China.

University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Sensors (Basel). 2016 Jun 16;16(6):888. doi: 10.3390/s16060888.

Abstract

This paper proposes an improved artificial bee colony algorithm named Weighted Global ABC (WGABC) algorithm, which is designed to improve the convergence speed in the search stage of solution search equation. The new method not only considers the effect of global factors on the convergence speed in the search phase, but also provides the expression of global factor weights. Experiment on benchmark functions proved that the algorithm can improve the convergence speed greatly. We arrive at the gas diffusion concentration based on the theory of CFD and then simulate the gas diffusion model with the influence of buildings based on the algorithm. Simulation verified the effectiveness of the WGABC algorithm in improving the convergence speed in optimal deployment scheme of gas sensors. Finally, it is verified that the optimal deployment method based on WGABC algorithm can improve the monitoring efficiency of sensors greatly as compared with the conventional deployment methods.

摘要

本文提出了一种改进的人工蜂群算法,即加权全局人工蜂群(WGABC)算法,旨在提高解搜索方程搜索阶段的收敛速度。新方法不仅考虑了全局因素对搜索阶段收敛速度的影响,还给出了全局因素权重的表达式。通过对基准函数的实验证明,该算法能大大提高收敛速度。基于计算流体动力学(CFD)理论得出气体扩散浓度,然后基于该算法模拟了有建筑物影响的气体扩散模型。仿真验证了WGABC算法在提高气体传感器最优部署方案收敛速度方面的有效性。最后,验证了基于WGABC算法的最优部署方法与传统部署方法相比,能大大提高传感器的监测效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5365/4934314/f0e6e70f3cd9/sensors-16-00888-g001.jpg

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