Data to intelligence: The role of data-driven models in wastewater treatment
Increasing energy efficiency in wastewater treatment plants (WWTPs) is becoming more
important. An emerging approach to addressing this issue is to exploit development in data …
important. An emerging approach to addressing this issue is to exploit development in data …
Review on machine learning-based bioprocess optimization, monitoring, and control systems
Abstract Machine Learning is quickly becoming an impending game changer for
transforming big data thrust from the bioprocessing industry into actionable output. However …
transforming big data thrust from the bioprocessing industry into actionable output. However …
New methods based on back propagation (BP) and radial basis function (RBF) artificial neural networks (ANNs) for predicting the occurrence of haloketones in tap …
Haloketones (HKs) is one class of disinfection by-products (DBPs) which is genetically toxic
and mutagenic. Monitoring HKs in drinking water is important for drinking water safety, yet it …
and mutagenic. Monitoring HKs in drinking water is important for drinking water safety, yet it …
Artificial neural networks for water quality soft-sensing in wastewater treatment: a review
This paper aims to present a comprehensive survey on water quality soft-sensing of a
wastewater treatment process (WWTP) based on artificial neural networks (ANNs). We …
wastewater treatment process (WWTP) based on artificial neural networks (ANNs). We …
Neural network-based uncertainty quantification: A survey of methodologies and applications
Uncertainty quantification plays a critical role in the process of decision making and
optimization in many fields of science and engineering. The field has gained an …
optimization in many fields of science and engineering. The field has gained an …
Prediction of effluent concentration in a wastewater treatment plant using machine learning models
Of growing amount of food waste, the integrated food waste and waste water treatment was
regarded as one of the efficient modeling method. However, the load of food waste to the …
regarded as one of the efficient modeling method. However, the load of food waste to the …
[HTML][HTML] Environmental odour management by artificial neural network–A review
Unwanted odour emissions are considered air pollutants that may cause detrimental
impacts to the environment as well as an indicator of unhealthy air to the affected individuals …
impacts to the environment as well as an indicator of unhealthy air to the affected individuals …
A comparative study of prediction models for alkali-activated materials to promote quick and economical adaptability in the building sector
Alkali-activated materials (AAMs) have recently gained attention as potentially useful
alternative binders that can reduce carbon dioxide emissions initiated by the production of …
alternative binders that can reduce carbon dioxide emissions initiated by the production of …
Data-derived soft-sensors for biological wastewater treatment plants: An overview
This paper surveys and discusses the application of data-derived soft-sensing techniques in
biological wastewater treatment plants. Emphasis is given to an extensive overview of the …
biological wastewater treatment plants. Emphasis is given to an extensive overview of the …
DNN model development of biogas production from an anaerobic wastewater treatment plant using Bayesian hyperparameter optimization
H Sadoune, R Rihani, FS Marra - Chemical Engineering Journal, 2023 - Elsevier
Deep neural networks have been regarded as accurate models to predict complex
fermentation processes due to their capacity to learn from a high number of data sets via …
fermentation processes due to their capacity to learn from a high number of data sets via …