A practical hybrid modelling approach for the prediction of potential fouling parameters in ultrafiltration membrane water treatment plant

CM Chew, MK Aroua, MA Hussain - Journal of Industrial and Engineering …, 2017 - Elsevier
In this work, a novel approach combining first principle equation of Darcy's law on cake
filtration and artificial neural network (ANN) predictive models were utilized to represent the …

A comparative assessment of predicting daily solar radiation using bat neural network (BNN), generalized regression neural network (GRNN), and neuro-fuzzy (NF) …

MM Lotfinejad, R Hafezi, M Khanali, SS Hosseini… - Energies, 2018 - mdpi.com
Highly accurate estimating of daily solar radiation by developing an intelligent and robust
model has been a subject of prominent concern for many researchers in the past few years …

Modelling the steel microstructure knowledge for in-silico recognition of phases using machine learning

S Gupta, A Banerjee, J Sarkar, M Kundu… - Materials Chemistry and …, 2020 - Elsevier
The present article demonstrates an effective approach to model the in-silico recognition of
phases in steel microstructures using the machine learning and image processing …

ANN-GA based parametric optimization of Al-TiB2 metal matrix composite material processing technique

A Sheelwant, PM Jadhav, SKR Narala - Materials Today Communications, 2021 - Elsevier
Over the years, aluminum metal matrix composites (AMMCs) have transitioned into a viable
replacement for traditional metals due to their exceptional strength-to-density ratio, higher …

Incorporation of prior knowledge in neural network model for continuous cooling of steel using genetic algorithm

S Chakraborty, PP Chattopadhyay, SK Ghosh… - Applied Soft …, 2017 - Elsevier
Artificial neural network model is developed for the prediction of phase transformation of
steel from austenite, and thus construction of the continuous cooling transformation (CCT) …

Improving the prediction of mechanical properties of aluminium alloy using data-driven class-based regression

N Bhat, AS Barnard, N Birbilis - Computational Materials Science, 2023 - Elsevier
The widespread use of aluminium alloys in the aerospace, transport and marine industries is
attributed to their desirable physical properties. The relationship between the alloy …

Designing UHMWPE hybrid composites using machine learning and metaheuristic algorithms

A Vinoth, S Dey, S Datta - Composite Structures, 2021 - Elsevier
The artificial replacement of hip joints comes into play when an individual is affected by
different types of arthritis or sudden trauma. Hip prosthesis involves the usage of ultra-high …

Early fault prediction of a wind turbine using a novel ANN training algorithm based on ant colony optimization

Y Eroğlu, SU Seçkiner - Journal of Energy Systems, 2019 - dergipark.org.tr
The technological developments in wind energy field have reduced the investment and the
operation costs. For this reason, wind farms have become more popular around the world …

Intelligent design optimization of age-hardenable Al alloys

S Dey, N Sultana, P Dey, SK Pradhan… - Computational Materials …, 2018 - Elsevier
Softening at elevated temperatures is known to be a serious problem in aluminium alloys
which restricts its wide span of application. Existing database on age-hardenable aluminium …

Natural computing-based designing of hybrid UHMWPE composites for orthopedic implants

V Arulraj, S Datta, JP Davim - Applied Sciences, 2022 - mdpi.com
The current study deals with the design of ultra-high molecular weight polyethylene
(UHMWPE) composites by integrating various micro and nanoparticles as reinforcements for …