Prediction of Pitch Using Neural Network with Unified Particle Swarm Optimization

被引：0

作者：

Qi, Wei-min ^{[1
]}

XianYu, Xiong-Feng ^{[1
]}

Zhou, Quan ^{[1
]}

Zhang, Xia ^{[1
]}

机构：

[1] Jianghan Univ, Sch Phys & Informat Engn, Wuhan, Peoples R China

来源：

2014 PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION (ICCSE 2014) | 2014年

关键词：

Pitch; Artificial neural network; Unified particle swarm optimization; Precipitation;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Particle swarm optimization (PSO) is a powerful optimization technique that has been applied to solve a number of complex optimization problems. The precipitation and deposition of crude oil polar fractions such as pitch in petroleum reservoirs reduce considerably the rock permeability and the oil recovery. In the present paper, the model based on a feed-forward artificial neural network (ANN) to predict pitch precipitation of the reservoir is pro-posed. After that ANN model was optimized by unified particle swarm optimization (UPSO). UPSO is used to decide the initial weights of the neural network. The UPSO-ANN model is applied to the experimental data reported in the literature. The performance of the UPSO-ANN model is compared with scaling model.

引用

页码：531 / 535

页数：5

共 50 条

[1] Neural network based unified particle swarm optimization for prediction of asphaltene precipitation
Ahmadi, Mohammad Ali
[J]. FLUID PHASE EQUILIBRIA, 2012, 314 : 46 - 51
[2] Traffic Signal Prediction Using Elman Neural Network and Particle Swarm Optimization
Ghasemi, J.
Rasekhi, J.
[J]. INTERNATIONAL JOURNAL OF ENGINEERING, 2016, 29 (11): : 1558 - 1564
[3] Autoignition Temperature Prediction Using an Artificial Neural Network with Particle Swarm Optimization
Juan A. Lazzús
[J]. International Journal of Thermophysics, 2011, 32
[4] Autoignition Temperature Prediction Using an Artificial Neural Network with Particle Swarm Optimization
Lazzus, Juan A.
[J]. INTERNATIONAL JOURNAL OF THERMOPHYSICS, 2011, 32 (05) : 957 - 973
[5] FOREX Rate Prediction Using Chaos, Neural Network and Particle Swarm Optimization
Pradeepkumar, Dadabada
Ravi, Vadlamani
[J]. ADVANCES IN SWARM INTELLIGENCE, ICSI 2014, PT II, 2014, 8795 : 363 - 375
[6] Modeling meteorological prediction using particle swarm optimization and neural network ensemble
Wu, Jiansheng
Jin, Long
Liu, Mingzhe
[J]. ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS, 2006, 3973 : 1202 - 1209
[7] Water Level Prediction using Artificial Neural Network with Particle Swarm Optimization Model
Panyadee, Pornnapa
Champrasert, Paskorn
Aryupong, Chuchoke
[J]. 2017 5TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY (ICOIC7), 2017,
[8] Construction of Neural Network-based Prediction Intervals using Particle Swarm Optimization
Quan, Hao
Srinivasan, Dipti
Khosravi, Abbas
[J]. 2012 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2012,
[9] Using Particle Swarm Optimization in Training Neural Network for Indoor Field Strength Prediction
Vilovic, Ivan
Burum, Niksa
Milic, Dorde
[J]. PROCEEDINGS ELMAR-2009, 2009, : 275 - 278
[10] Applying Neural Network with Particle Swarm Optimization for Energy Requirement Prediction
Chang, Jianxia
Xu, Xiaoyuan
[J]. 2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, : 6161 - 6163

← 1 2 3 4 5 →