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Defect detection of wire rope for oil well based on adaptive angle

Fracture and Structural Integrity, 2015
This paper uses a digital image processing method which is based on texture feature of steel cable to detect the fracture of steel wire. At first, it uses a modified homomorphic filtering method to eliminate environment heterogeneous shining.
Zhang Jijun, Meng Xiangqing
doaj

Application of back propagation neural network optimized by different algorithms in prediction of Mooney viscosity of ethylene-propylene-diene monomer compound

Hecheng xiangjiao gongye
Genetic algorithm (GA) and particle swarm optimization (PSO) were used to optimize the back propagation（BP） neural network to establish the prediction model of Mooney viscosity of ethylene-propylene-diene monomer (EPDM) compound, and the error of the ...
LI Gao-wei, LI Jia, ZHU Jin-mei, JIAN Ran-ran, MIAO Qing, ZENG Xian-kui
doaj +1 more source

Application of improved BP neural network in fault detection of mine ventilation system

Gong-kuang zidonghua, 2013
For problem that step of traditional learning algorithm of BP neural network is difficult to determine, the paper proposed a method of using BP neural network based on RLS algorithm to detect fault of mine ventilation system.
ZHANG Fei, HE Ya-qin, ZHANG Ke
doaj

Financial production marketing prediction based on optimization GA-BP neural network

Tongxin xuebao, 2014
The traditional BP neural network has some application problems.For example,the network structure parameter is too dependent on experience and easy to fall into local solution.In order to improve the application defects of BP neural network model,the ...
Xin JIN, Yi-an PAN, Jing WU
doaj +2 more sources

Application of deep learning for division of petroleum reservoirs

MATEC Web of Conferences, 2018
Traditional methods of dividing petroleum reservoirs are inefficient, and the accuracy of onehidden-layer BP neural network is not ideal when applied to dividing reservoirs.
Qin Yaqiong, Ye Zhaohui, Zhang Conghui
doaj +1 more source

Prediction of Variable-speed Compressor Power Based on Particle Swarm Optimization and Back Propagation Neural Network

Zhileng xuebao, 2020
A prediction method based on simulation is proposed to reduce the difficulty and the large error in measuring the power of variable-speed compressor. The threshold and weight of a back propagation (BP) neural network were initialized by particle swarm ...
Gong Qijian +4 more
doaj

Predicting peak particle velocity in pre-splitting of gas-producing devices using improved particle swarm optimization algorithm

Scientific Reports
Advance prediction and control of vibration velocity during blasting construction is essential to protect the tunnel and surrounding buildings. In this study, we propose an Improved Particle Swarm Optimization (IPSO) Backpropagation (BP) Neural Network ...
Yawen Cao +5 more
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Predicting Soft Soil Settlement with a FAGSO-BP Neural Network Model

Buildings
Aiming at the problem that it is difficult to consider the prediction of foundation settlement in the case of multi-parameter coupling effect by theoretical formulas and numerical analysis, the fireworks algorithm with gravitational search operator ...
Binhui Ma +7 more
doaj +1 more source

Lithium battery SOC estimation based on improved sparrow search algorithm and backpropagation neural network

AIP Advances
Accurate state-of-charge (SOC) estimation is crucial for optimal battery management. This paper proposes a novel method, the Improved Sparrow Search Algorithm-Backpropagation (ISSA-BP) neural network, to address the issue of low estimation accuracy ...
Yingying Zhang +4 more
doaj +1 more source

Retraction: Application of IRSA-BP neural network in diagnosing diabetes. [PDF]

PLoS One
PLOS One Editors.
europepmc +1 more source

genetic algorithm
neural network
physics

particle swarm optimization