Optimisation of machining parameters of AISI 304L stainless steel with the least error method using Taguchi, RSM, and ANN

Nehri, Yunus Emre; Oral, Ali; Toktaş, Alaaddin

doi:10.1080/14484846.2024.2366605

Australian Journal of Mechanical Engineering

2024

DOI: 10.1080/14484846.2024.2366605

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Optimisation of machining parameters of AISI 304L stainless steel with the least error method using Taguchi, RSM, and ANN

Yunus Emre Nehri,

Ali Oral,

Alaaddin Toktaş

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Utilising Artificial Intelligence to Predict Membrane Behaviour in Water Purification and Desalination

Shahouni,

Abbasi,

Dibaj

et al. 2024

Water

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Water scarcity is a critical global issue, necessitating efficient water purification and desalination methods. Membrane separation methods are environmentally friendly and consume less energy, making them more economical compared to other desalination and purification methods. This survey explores the application of artificial intelligence (AI) to predict membrane behaviour in water purification and desalination processes. Various AI platforms, including machine learning (ML) and artificial neural networks (ANNs), were utilised to model water flux, predict fouling behaviour, simulate micropollutant dynamics and optimise operational parameters. Specifically, models such as convolutional neural networks (CNNs), recurrent neural networks (RNNs) and support vector machines (SVMs) have demonstrated superior predictive capabilities in these applications. This review studies recent advancements, emphasising the superior predictive capabilities of AI models compared to traditional methods. Key findings include the development of AI models for various membrane separation techniques and the integration of AI concepts such as ML and ANNs to simulate membrane fouling, water flux and micropollutant behaviour, aiming to enhance wastewater treatment and optimise treatment and desalination processes. In conclusion, this review summarised the applications of AI in predicting the behaviour of membranes as well as their strengths, weaknesses and future directions of AI in membranes for water purification and desalination processes.

show abstract

Utilising Artificial Intelligence to Predict Membrane Behaviour in Water Purification and Desalination

Shahouni,

Abbasi,

Dibaj

et al. 2024

Water

View full text Add to dashboard Cite

show abstract

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Optimisation of machining parameters of AISI 304L stainless steel with the least error method using Taguchi, RSM, and ANN

Cited by 1 publication

References 28 publications

Utilising Artificial Intelligence to Predict Membrane Behaviour in Water Purification and Desalination

Utilising Artificial Intelligence to Predict Membrane Behaviour in Water Purification and Desalination

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