Use of neural network for modeling of non-linear process integration technology in chemical engineering

被引：10
作者：
Abilov, A [1 ]
Zeybek, Z
机构：
[1] Ankara Univ, Dept Elect Engn, TR-06100 Ankara, Turkey
[2] Ankara Univ, Dept Chem Engn, TR-06100 Ankara, Turkey
来源：
CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION | 2000年 / 39卷 / 05期
关键词：
industrial petrol refinery complex; neural network; modeling; non-linear processes; integration technology;
D O I：
10.1016/S0255-2701(00)00092-1
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
The topology of an industrial petrol refinery complex (PRC) has been formed as a non-linear function by neural network. Starting from the topology of the integration technology' various choices of production and consumption rates were evaluated both technically and economically on the basis of non-linear material balances. The calculation of the weights of the units of PRC and the determination of the dependence of these units on each other have been performed according to the market conditions. The pertinent equation and the optimal parameters are presented. (C) 2000 Elsevier Science S.A. All rights reserved.
引用
收藏
页码：449 / 458
页数：10
相关论文
共 50 条
  • [21] Neural Network-Based Successive Interference Cancellation for Non-Linear Bandlimited Channels
    Plabst, Daniel
    Prinz, Tobias
    Diedolo, Francesca
    Wiegart, Thomas
    Boecherer, Georg
    Hanik, Norbert
    Kramer, Gerhard
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2025, 73 (03) : 1847 - 1861
  • [22] Non-linear self-tuning control of chemical reactors with input and process constraints
    Radhakrishnan, TK
    PROCESS CONTROL AND QUALITY, 1997, 9 (1-3) : 39 - 49
  • [23] Non-linear dynamics on VSF-Network
    Kakemoto, Y
    Kaji, T
    Nakasuka, S
    KNOWLEDGE-BASED SOFTWARE ENGINEERING, 2004, 108 : 177 - 188
  • [24] Piecewise Linear Neural Network for Process Control in Industrial Environment
    Dolezel, Pelf
    Gago, Lumir
    PROCEEDINGS OF THE 2016 17TH INTERNATIONAL CARPATHIAN CONTROL CONFERENCE (ICCC), 2016, : 161 - 165
  • [25] Approximation of a Neural Network Controller Based on Model Reference Technique to Identify a Non-linear System
    Mandal, Priyaranjan
    Deb, Anish
    2014 INTERNATIONAL CONFERENCE ON CONTROL, INSTRUMENTATION, ENERGY & COMMUNICATION (CIEC), 2014, : 21 - 25
  • [26] Progressive framework for deep neural networks: from linear to non-linear
    Jie S.
    Zhicheng Z.
    Fei S.
    Anni C.
    1600, Beijing University of Posts and Telecommunications (23): : 1 - 7
  • [27] A Note on Fractional-Order Non-Linear Controller: Possible Neural Network Approach to Design
    Petras, Ivo
    2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2016, : 603 - 608
  • [28] Prediction of Saturated Vapor Pressures Using Non-Linear Equations and Artificial Neural Network Approach
    Honarmand, Mehrdad
    Sanjari, Ehsan
    Badihi, Hamidreza
    JOURNAL OF MATHEMATICS AND COMPUTER SCIENCE-JMCS, 2014, 8 (04): : 343 - 358
  • [29] Progressive framework for deep neural networks: from linear to non-linear
    Shao Jie
    Zhao Zhicheng
    Su Fei
    Cai Anni
    TheJournalofChinaUniversitiesofPostsandTelecommunications, 2016, 23 (06) : 1 - 7
  • [30] Non-linear chemical process modelling and application in epichlorhydrine production plant using wavelet networks
    Huang, DX
    Jin, YH
    Zhang, J
    Morris, AJ
    CHINESE JOURNAL OF CHEMICAL ENGINEERING, 2002, 10 (04) : 435 - 443
12345