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All Journal Techno.Com: Jurnal Teknologi Informasi JAIS (Journal of Applied Intelligent System) JURIKOM (Jurnal Riset Komputer) Abdimasku : Jurnal Pengabdian Masyarakat Journal of Multiscale Materials Informatics
Prabowo, Wahyu Aji Eko
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Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Social Sciences

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Journal : JAIS (Journal of Applied Intelligent System)

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Broad Learning System for Investigating Corrosion Inhibition Efficiency of Heterocyclic Compounds Akrom, Muhamad; Prabowo, Wahyu Aji Eko
Journal of Applied Intelligent System Vol. 4 No. 2 (2019): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v4i2.12487

Abstract

This study explores the use of Broad Learning Systems (BLS) to predict the corrosion inhibition efficiency (CIE) of heterocyclic compounds, addressing limitations of deep neural networks (DNNs) such as vanishing gradients and computational inefficiency. BLS prioritizes network width over depth, enabling faster learning and improved generalization. Trained on quantum chemical properties (QCPs) of 192 heterocyclic compounds, BLS outperformed multilayer perceptron neural networks (MLPNN) and random forest (RF) models, achieving lower mean absolute error (MAE: 1.41), root mean square error (RMSE: 1.79), and higher R² (0.993). Predicted CIE values for quinoxaline derivatives (95.39% and 94.05%) aligned closely with experimental data. This study demonstrates the potential of BLS as an efficient, accurate, and scalable approach for predicting corrosion inhibition capabilities, contributing to advancements in corrosion science and environmentally friendly solutions. Keywords - machine learning, broad learning system, neural network, corrosion.
Co-Authors Achmad Wahid Kurniawan Adi, Ilham Arif Kuncoro Ajisaputra, Faris Prasetya Akrom, Muhamad Ayu Pertiwi Harun Al Azies Hidayat, Novianto Nur Hidayatulloh, Ryan Moch Anjas Aprihartha Muhammad Naufal, Muhammad Noor Ageng Setiyanto, Noor Ageng Safitri, Aprilyani Nur Sudibyo, Usman Trisnapradika, Gustina Alfa