Comparison of artificial neural network and multi-kinetic models to predict optimum retention time for dairy wastewater treatment in the integrated fixed-film activated sludge-Reference-Cited by-同舟云学术

Comparison of artificial neural network and multi-kinetic models to predict optimum retention time for dairy wastewater treatment in the integrated fixed-film activated sludge

Published:2020-06-29 Issue: Volume: Page:1-15
ISSN:0306-7319
Container-title:International Journal of Environmental Analytical Chemistry
language:en
Short-container-title:International Journal of Environmental Analytical Chemistry

Author:

Shokri Dariyan Fatemeh¹,Eslami Akbar¹²,Aghayani Ehsan³,Pourakbar Mojtaba⁴,Oghazyan Ali¹

Affiliation:

1. Department of Environmental Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran

2. Environmental and Occupational Hazards Control Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran

3. Department of Environmental Health Engineering, Abadan School of Medical Sciences, Abadan, Iran

4. Department of Environmental Health Engineering, Maragheh University of Medical Sciences, Maragheh, Iran

Funder

Environmental and Occupational Hazards Control Research Center

Publisher

Informa UK Limited

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health,Pollution,Soil Science,Waste Management and Disposal,Water Science and Technology,Environmental Chemistry,Analytical Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/03067319.2020.1785442

Reference30 articles.

1. The investigation of dairy industry wastewater treatment in a biological high performance membrane system

2. Microalgal biomass generation by phycoremediation of dairy industry wastewater: An integrated approach towards sustainable biofuel production

3. Sustainability of dairy and soy processing: A review on wastewater recycling

4. Process analysis and optimization of single stage flexible fibre biofilm reactor treating milk processing industrial wastewater using response surface methodology (RSM)

5. Seasonal and wastewater stream variation of trace organic compounds in a dairy processing plant aerobic bioreactor

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning (ML): An emerging tool to access the production and application of biochar in the treatment of contaminated water and wastewater;Groundwater for Sustainable Development;2024-08

2. Biochar-based geopolymer nanocomposite for COD and phenol removal from agro-industrial biorefinery wastewater: Kinetic modelling, microbial community, and optimization by response surface methodology;Chemosphere;2023-10

3. Digital interoperability and transformation using Industry 4.0 technologies in the dairy industry: An SLR and bibliometric analysis;Logforum;2023-09-30

4. Machine learning-based design and monitoring of algae blooms: Recent trends and future perspectives – A short review;Critical Reviews in Environmental Science and Technology;2023-09-07

5. A cascaded modeling approach for comprehensive reaction state perception of a hydrometallurgical reactor;Engineering Applications of Artificial Intelligence;2023-09