Final sulfur content prediction model based on neural network and multiple linear regression for hot metal predesulfurization

被引：0
|
作者：
Zhang, Hui-Shu [1 ]
Zhan, Dong-Ping [1 ]
Jiang, Zhou-Hua [1 ]
机构：
[1] School of Materials and Metallurgy, Northeastern University, Shenyang 110004, China
来源：
Dongbei Daxue Xuebao/Journal of Northeastern University | 2006年 / 27卷 / SUPPL. 2期
关键词：
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：5 / 7
相关论文
共 50 条
  • [41] Artificial Neural Network and Multiple Linear Regression for Prediction and Classification of Sustainability of Sodium and Potassium Coronates
    Bondarev, N. V.
    RUSSIAN JOURNAL OF GENERAL CHEMISTRY, 2019, 89 (07) : 1438 - 1446
  • [42] Daily Suspended Sediment Discharge Prediction Using Multiple Linear Regression and Artificial Neural Network
    Uca
    Toriman, Ekhwan
    Jaafar, Othman
    Maru, Rosmini
    Arfan, Amal
    Ahmar, Ansari Saleh
    JOINT WORKSHOP OF KO2PI & 2ND INTERNATIONAL CONFERENCE ON MATHEMATICS, SCIENCE, TECHNOLOGY, EDUCATION, AND THEIR APPLICATIONS (2ND ICMSTEA), 2018, 954
  • [43] A Prediction Model Based on Linear Regression and Artificial Neural Network Analysis of the Hairiness of Polyester Cotton Winding Yarn
    Bo, Zhao
    ADVANCES IN MULTIMEDIA, SOFTWARE ENGINEERING AND COMPUTING, VOL 1, 2011, 128 : 97 - 103
  • [44] Prediction of wetland area and depth using linear regression model and artificial neural network based cellular automata
    Saha, Tamal Kanti
    Pal, Swades
    Sarkar, Raju
    ECOLOGICAL INFORMATICS, 2021, 62
  • [45] Prediction Model of Soil Heavy Metal Content Based on Particle Swarm Algorithm Optimized Neural Network
    Duan, Cuiqing
    Wang, Baoqiang
    Li, Jinxiu
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [46] Prediction of Total Soluble Solids Content Using Tomato Characteristics: Comparison Artificial Neural Network vs. Multiple Linear Regression
    Kabas, Aylin
    Ercan, Ugur
    Kabas, Onder
    Moiceanu, Georgiana
    APPLIED SCIENCES-BASEL, 2024, 14 (17):
  • [47] Prediction of loquat soluble solids and titratable acid content using fruit mineral elements by artificial neural network and multiple linear regression
    Huang, Xiao
    Wang, Huakun
    Luo, Wenjie
    Xue, Song
    Hayat, Faisal
    Gao, Zhihong
    SCIENTIA HORTICULTURAE, 2021, 278
  • [48] Dissolved oxygen content interval prediction based on auto regression recurrent neural network
    Jiande Huang
    Yue Huang
    Shahbaz Gul Hassan
    Longqin Xu
    Shuangyin Liu
    Journal of Ambient Intelligence and Humanized Computing, 2023, 14 : 7255 - 7264
  • [49] Dissolved oxygen content interval prediction based on auto regression recurrent neural network
    Huang, Jiande
    Huang, Yue
    Hassan, Shahbaz Gul
    Xu, Longqin
    Liu, Shuangyin
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021, 14 (6) : 7255 - 7264
  • [50] Prediction of Fatigue Strength in Steels by Linear Regression and Neural Network
    Shiraiwa, Takayuki
    Miyazawa, Yuto
    Enoki, Manabu
    MATERIALS TRANSACTIONS, 2019, 60 (02) : 189 - 198
12345