Genetic algorithm and artificial neural network model for prediction of discoloration dye from an electro-oxidation process in a press-type reactor

被引：15
|
作者：
Picos, Alain [1 ]
Peralta-Hernandez, Juan M. [1 ]
机构：
[1] Univ Guanajuato, Dept Quim, Div Ciencias Nat & Exactas, Campus Guanajuato, Guanajuato 36050, Gto, Mexico
来源：
WATER SCIENCE AND TECHNOLOGY | 2018年 / 78卷 / 04期
关键词：
artificial neural network; dye discoloration; electro-oxidation process; model prediction; press-type reactor; WASTE-WATER TREATMENT; SLUDGE BLANKET REACTOR; DOPED DIAMOND ANODE; ELECTROCATALYTIC DEGRADATION; ELECTROCHEMICAL OXIDATION; COD REMOVAL; AZO-DYE; OPTIMIZATION; FENTON; PERFORMANCE;
D O I：
10.2166/wst.2018.370
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
This study evaluates the effectiveness of an artificial neural network-genetic algorithm (ANN-GA) artificial intelligence (AI) model in the prediction of behavior and optimization of an electro-oxidation pilot press-type reactor, which treats a synthetic wastewater prepared with a dye. The ANN was built from real experimental data using as input the following variables: time, flow, j, dye concentration, and as output discoloration. The performance of the ANN was measured with MAPE (8.3868%), calculated from real and predicted values. The coupled AI model was used to find the best operational conditions: discoloration efficiency (above 90%) at j = 27 mA/cm(2) and dye concentration of 230 mg/L.
引用
收藏
页码：925 / 935
页数：11
相关论文
共 32 条
  • [1] Modelling the chlorophenol removal from wastewater via reverse osmosis process using a multilayer artificial neural network with genetic algorithm
    Mohammad, Abdulrahman Th
    Al-Obaidi, Mudhar A.
    Hameed, Emad Majeed
    Basheer, Basil N.
    Mujtaba, Iqbal M.
    JOURNAL OF WATER PROCESS ENGINEERING, 2020, 33
  • [2] Optimization of photocatalytic oxidation reactor for air purifier design: Application of artificial neural network and genetic algorithm
    Malayeri, Mojtaba
    Nasiri, Fuzhan
    Haghighat, Fariborz
    Lee, Chang-Seo
    CHEMICAL ENGINEERING JOURNAL, 2023, 462
  • [3] Modelling and optimizing an electrochemical oxidation process using artificial neural network, genetic algorithm and particle swarm optimization
    Liu, Banghai
    Jin, Chunji
    Wan, Jiteng
    Li, Pengfang
    Yan, Huanxi
    JOURNAL OF THE SERBIAN CHEMICAL SOCIETY, 2018, 83 (03) : 379 - 390
  • [4] Decolourization of Disperse Blue 3 Dye by Electro Coagulation Process Using Al and Fe Electrodes -Application of the Artificial Neural Network Model
    Salah, Asma
    Bensmaili, Aicha
    Trari, Mohamed
    IRANIAN JOURNAL OF CHEMISTRY & CHEMICAL ENGINEERING-INTERNATIONAL ENGLISH EDITION, 2022, 41 (04): : 1175 - 1185
  • [5] Modelling and optimization of fenton process for decolorization of azo dye (DR16) at microreactor using artificial neural network and genetic algorithm
    Ahari, Jafar Sadeghzadeh
    Sadeghi, Masoud
    Salooki, Mahdi Koolivand
    Esfandyari, Morteza
    Rahimi, Masoud
    Anahid, Sanaz
    HELIYON, 2024, 10 (13)
  • [6] A Study on Prediction of Process Parameters of Shot Peen Forming Using Artificial Neural Network Optimized by Genetic Algorithm
    Wang, T.
    Wang, J. B.
    Zhang, X. J.
    Liu, C.
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2021, 46 (08) : 7349 - 7361
  • [7] A Study on Prediction of Process Parameters of Shot Peen Forming Using Artificial Neural Network Optimized by Genetic Algorithm
    T. Wang
    J. B. Wang
    X. J. Zhang
    C. Liu
    Arabian Journal for Science and Engineering, 2021, 46 : 7349 - 7361
  • [8] A genetic algorithm model based on artificial neural network for prediction of the axillary lymph node status in breast cancer
    Karakis, R.
    Tez, M.
    Kilic, Y. A.
    Kuru, Y.
    Guler, I.
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2013, 26 (03) : 945 - 950
  • [9] Appraisal of artificial neural network-genetic algorithm based model for prediction of the power provided by the agricultural tractors
    Taghavifar, Hamid
    Mardani, Aref
    Hosseinloo, Ashkan Haji
    ENERGY, 2015, 93 : 1704 - 1710
  • [10] Prediction Model of Strength of Al-Mg-Si Alloy Based on Artificial Neural Network and Genetic Algorithm
    Li Lingxin
    Jiang Haitao
    Wu Xiaoyan
    Li Jun
    Tian Shiwei
    RARE METAL MATERIALS AND ENGINEERING, 2023, 52 (03) : 929 - 936
1234