Intelligent upgrade of waste-activated sludge dewatering process based on artificial neural network model: Core influential factor identification and non-experimental prediction of sludge dewatering performance.
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- Type
- article
- Published
- 2023-09-13
- Cited by
- 17
- References
- 40
- OpenAlex
- https://openalex.org/W37714087
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:261847044
Keywords
Poverty, Economic growth, Rural development, Political science, Developing country
References
- A novel hybrid learning algorithm for full Bayesian approach of artificial neural networks
- Evaluation of PCA and Gamma test techniques on ANN operation for weekly solid waste prediction.
- Contribution of extracellular polymeric substances (EPS) and their subfractions to the sludge aggregation in membrane bioreactor coupled with worm reactor.
- Multivariate Econometric Approach for Solid Waste Generation Modeling: Impact of Climate Factors
- Sewage Sludge: An Important Biological Resource for Sustainable Agriculture and Its Environmental Implications
- Contribution of extracellular polymeric substances (EPS) to the sludge aggregation.
- Conditioning of alum sludge with polymer and gypsum
- Characterization of activated sludge exocellular polymers using several cation-associated extraction methods.
- A review on sludge conditioning by sludge pre-treatment with a focus on advanced oxidation
- Application of amphoteric polyelectrolytes for sludge dewatering
- A review of the properties of biosludge and its relevance to enhanced dewatering processes
- A framework development for predicting the longitudinal dispersion coefficient in natural streams using an artificial neural network
- Influence of loosely bound extracellular polymeric substances (EPS) on the flocculation, sedimentation and dewaterability of activated sludge.
- Study of the influence of geotechnical parameters on the TBM performance in Tehran–Shomal highway project using ANN and SPSS
- Prediction of municipal solid waste generation with combination of support vector machine and principal component analysis: A case study of Mashhad
- Effect of proteins, polysaccharides, and particle sizes on sludge dewaterability.
- Bound water content of biological sludges in relation to filtration and dewatering
- Characterization of Exocellular Protein and Its Role in Bioflocculation
- Dewatering in biological wastewater treatment: A review.
- Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate: A case study of Fars province, Iran.
Cited by
- Physical conditioning methods for sludge deep dewatering: A critical review.
- Soft sensor for the dry solid content in thickened primary sludge
- Machine learning in sludge Treatment: Applications, mechanisms, and prospects
- State-of-the-Art Decarbonization in Sludge Thermal Treatments for Electrical Power Generation Considering Sensors and the Application of Artificial Intelligence
- Research status and prospects of using machine learning for promoting carbon emission reduction in wastewater treatment processes: A review
- Reconstructing sludge microstructure for deep dewatering: A critical review of mechanisms and prospects of skeleton construction technology.
- The Informal Language Learning of Female Saudi Undergraduates
- ノンフォーマル教育援助における参加型評価手法の活用 「利害関係者が評価過程に評価主体として関わること」の意義
- Intelligent framework integrating feature engineering and indicator-specific optimization for predicting wastewater treatment plant influent quality and flow
- Evaluation of greenhouse gas emissions from sludge treatment in Apulia, Southern Italy
- Waste sludge conditioning for the enhanced dewaterability: A review of key factors, significant methods, post-disposal paths, and artificial intelligence integration
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