• Mechanical Engineering •

### Prediction method of tailing dam groundwater levels based on improved PSO-BP neural network

Diankun ZHENG1(),Tongle XU1,*(),Zhaojie YIN1,Qingmin MENG2

1. 1. Mechanical Engineering School, Shandong University of Technology, Zibo 255049, Shandong, China
2. Shanbo Anjifu Gear Motor Co., Ltd., Zibo 255200, Shandong, China
• Received:2017-09-04 Online:2019-06-20 Published:2019-06-27
• Contact: Tongle XU E-mail:zdk5287@163.com;xutongle@163.com
• Supported by:
山东省自然科学基金资助项目(ZR2013FM005);淄博市科学技术发展计划资助项目(JY20151587)

Abstract:

To solve the low convergence speed and poor precision problem of the traditional prediction algorithm, an improved particle swarm optimization(IPSO) algorithm was proposed. The inertia factor ω and the accelerating factor c1 and c2 of the algorithm were dynamically adjusted during the searching process to improve the optimization effectiveness. The weights and thresholds of back propagation(BP) network were optimized by the improved algorithm. And the prediction model of groundwater levels in tailing dam was built and verified according to its instance data. The test results showed that the convergence speed of algorithm and the accuracy of prediction model was improved.

CLC Number:

• TD76
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