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Environmental assessment of world bank projects in Yanhe basin based on evidence synthesis trained by particle swarm optimization neural network

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1 Author(s)
Chen Li ; Anhui Inst. of Archit. & Ind., Hefei, China

Particle swarm optimization (PSO) algorithm can be used to solve optimization problem. The Back Propagation (BP) network convergence speed is very fast after being optimized by PSO, and it can also avoid the defects of local infinitesimal and constringent plateau. This text uses a project in Yanhe basin as an example, and applies evidence synthesis trained by particle swarm optimization neural network to complete a project environmental quality assessment. Theoretical analysis and experimental results show that the coefficient of the amendment is more reasonable and more accuracy.

Published in:

Natural Computation (ICNC), 2010 Sixth International Conference on  (Volume:1 )

Date of Conference:

10-12 Aug. 2010