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Waste slag dam deformation prediction method based on DPSO-ANFIS

A prediction method and preprocessing technology, applied in prediction, biological neural network model, computational model, etc., can solve problems such as low accuracy and poor generalization performance, and achieve reliable stability, high accuracy, and excellent comprehensive performance. Effect

Inactive Publication Date: 2021-07-20
陕西镇安抽水蓄能有限公司 +1
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AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a method for predicting the deformation of spoil dams based on DPSO-ANFIS, which solves the problems of low accuracy and poor generalization performance of existing spoil dam deformation prediction methods

Method used

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  • Waste slag dam deformation prediction method based on DPSO-ANFIS
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  • Waste slag dam deformation prediction method based on DPSO-ANFIS

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Embodiment

[0110] In this example, a spoil dam is located in Ximogou, Zhen’an County, Shangluo City. The spoil dam is mainly used for excavation and waste slag stacking of roads connecting the upper and lower reservoirs, external access roads and hydraulic tunnels, and as a later transfer yard. The spoil dam covers an area of ​​81,200 m2, and the total amount of spoil is 4,754,100 m 3 , is a super-class 1 super-large slag yard. The slag dump is divided into two platforms with elevations of 1005m and 949m respectively. The design drawing of the spoil dam is shown in image 3 shown.

[0111] Step 1, analyzing the monitoring data of the horizontal displacement of the dam crest, and preprocessing the original data;

[0112] Select the monitoring data of EL1095, EL1070 and EL1016 construction platforms of spoil dam 1# along the gully and near the left side of the ditch as data samples, and the monitoring frequency is once a day. This time series contains a total of 470 sets of data from Ju...

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Abstract

The invention discloses a waste slag dam deformation prediction method based on DPSO-ANFIS; the method comprises the following steps: 1, monitoring the original data of a waste slag dam, and carrying out the preprocessing of the original data; 2, establishing an adaptive fuzzy neural network system, and assigning network parameters in the system; 3, optimizing parameters of the adaptive fuzzy neural network in the step 2; and 4, substituting the abandoned slag dam data preprocessed in the step 1 into the self-adaptive fuzzy neural network for training and prediction, at the moment, enabling parameters in the self-adaptive fuzzy neural network to be optimal through the step 3, calculating a prediction precision value, and comparing prediction effects of measurement points at different positions. The prediction method has the advantages of high accuracy, good generalization, reliable stability and excellent engineering practical comprehensive performance.

Description

technical field [0001] The invention belongs to the technical field of deformation prediction of spoil dams, and in particular relates to a deformation prediction method of spoil dams based on DPSO-ANFIS. Background technique [0002] With the development of society and economy, modern water conservancy engineering technology is constantly innovating, and the construction of reservoirs and dams has become the main content of current water conservancy projects. Using the actual monitoring data of the dam to establish a deformation prediction model is a means of effective safety monitoring of the dam, which is of great significance for monitoring the safe operation of the dam. For dam deformation monitoring data with complex nonlinear characteristics, Adaptive Network-based Fuzzy Inference System (ANFIS) has the characteristics of structure and parameter identification, adaptively generates fuzzy rules, and optimizes membership and output functions. According to the input inf...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06K9/62G06N3/00G06N3/04
CPCG06Q10/04G06Q50/06G06N3/006G06N3/043G06F18/23
Inventor 李作舟薛方方刘杨郑成成杨杰马春辉冉蠡秦鸿哲赵强姜泽明胡广柱
Owner 陕西镇安抽水蓄能有限公司
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