Development of QSAR-based (MLR/ANN) predictive models for effective design of pyridazine corrosion inhibitors

TW Quadri, LO Olasunkanmi, ED Akpan… - Materials Today …, 2022 - Elsevier
Twenty pyridazine derivatives with previously reported experimental data were utilized to
develop predictive models for the anticorrosion abilities of pyridazine-based compounds …

Effectiveness analysis of PMSM motor rolling bearing fault detectors based on vibration analysis and shallow neural networks

P Ewert, T Orlowska-Kowalska, K Jankowska - Energies, 2021 - mdpi.com
Permanent magnet synchronous motors (PMSMs) are becoming more popular, both in
industrial applications and in electric and hybrid vehicle drives. Unfortunately, like the …

DeepSHM: A deep learning approach for structural health monitoring based on guided Lamb wave technique

V Ewald, RM Groves… - Sensors and Smart …, 2019 - spiedigitallibrary.org
In our previous work, we demonstrated how to use inductive bias to infuse a convolutional
neural network (CNN) with domain knowledge from fatigue analysis for aircraft visual NDE …

Impact of non-linear high-power amplifiers on cooperative relaying systems

E Balti, M Guizani - IEEE Transactions on Communications, 2017 - ieeexplore.ieee.org
In this paper, we investigate the impact of the high-power amplifier non-linear distortion on
multiple relay systems by introducing the soft envelope limiter, traveling wave tube amplifier …

River suspended sediment prediction using various multilayer perceptron neural network training algorithms—a case study in Malaysia

MR Mustafa, RB Rezaur, S Saiedi, MH Isa - Water resources management, 2012 - Springer
Estimation of suspended sediment discharge in rivers has a vital role in dealing with water
resources problems and hydraulic structures. In this study, a Multilayer Perceptron (MLP) …

Predicting protection capacities of pyrimidine-based corrosion inhibitors for mild steel/HCl interface using linear and nonlinear QSPR models

TW Quadri, LO Olasunkanmi, OE Fayemi… - Journal of Molecular …, 2022 - Springer
Pyrimidine compounds have proven to be effective and efficient additives capable of
protecting mild steel in acidic media. This class of organic compounds often functions as …

Predicting of blasting vibrations in Sarcheshmeh copper mine by neural network

HB Amnieh, MR Mozdianfard, A Siamaki - Safety Science, 2010 - Elsevier
Artificial Neural Networks (ANN) have proven to be an effective tool for solving complex
engineering problems requiring estimation, pattern recognition, and classification of …

Compressive strength prediction of stabilized dredged sediments using artificial neural network

VQ Tran - Advances in Civil Engineering, 2021 - Wiley Online Library
Stabilized dredged sediments are used as a backfilling material to reduce construction costs
and a solution to environmental protection. Therefore, the compressive strength is an …

The assessment of response surface methodology (RSM) and artificial neural network (ANN) modeling in dry flue gas desulfurization at low temperatures

R Makomere, H Rutto, L Koech - Journal of Environmental Science …, 2023 - Taylor & Francis
The performance of a flue gas desulfurization (FGD) system is characterized by SO2
removal efficiency (Y 1) and reagent conversion (Y 2). Achieving a near-perfect reaction …

Artificial neural network based vertical handoff algorithm for reducing handoff latency

A Çalhan, C Çeken - Wireless personal communications, 2013 - Springer
One of the most challenging topics for next generation wireless networks is vertical handoff
concept since several wireless technologies are assumed to cooperate. Plenty of …