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Model Optimasi SVM Dengan PSO-GA dan SMOTE Dalam Menangani High Dimensional dan Imbalance Data Banjir

Raenald Syaputra, Taghfirul Azhima Yoga Siswa, Wawan Joko Pranoto • Teknika (2024)

Banjir merupakan salah satu bencana alam yang sering terjadi di Indonesia, termasuk di Kota Samarinda dengan 18-33 titik desa terdampak dari tahun 2018-2021. Penggunaan machine learning dalam mengklasifikasi bencana banjir sangat penting un...

DOAJ Open Access (DOAJ) DOI: 10.34148/teknika.v13i2.876

Lyapunov analysis of data-driven models of high dimensional dynamics using reservoir computing: Lorenz-96 system and fluid flow

Miki U Kobayashi, Kengo Nakai, Yoshitaka Saiki • Journal of Physics: Complexity (2024)

We computed the Lyapunov spectrum and finite-time Lyapunov exponents of a data-driven model constructed using reservoir computing. This analysis was performed for two dynamics that exhibit a highly dimensionally unstable structure. We focus...

DOAJ Open Access (DOAJ) DOI: 10.1088/2632-072X/ad5264

High Dimensional QSAR Study of Mild Steel Corrosion Inhibition in acidic medium by Furan Derivatives

Abdo M. Al-Fakih, Madzlan Aziz, Hassan H. Abdallah, Zakariya Y. Algamal et al. • International Journal of Electrochemical Science (2015)

The inhibition of mild steel corrosion in 1 M HCl by 17 furan derivatives was investigated experimentally using potentiodynamic polarization measurements. The furan derivatives inhibit the mild steel corrosion. The experimental inhibition e...

DOAJ Open Access (DOAJ) DOI: 10.1016/S1452-3981(23)06562-8

Framework for Implementing Quantum Neural Networks in Wireless Communications

Salik Siddiqui, Justin Holzer, Joshua Malcarne, Galahad M. B. Wernsing et al. • IEEE Access (2025)

While quantum computing is already being employed in different domains to solve large scale and highly complex optimization problems, the wireless communications community has only recently begun exploring the potential of Quantum Machine L...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3572416

On Application of Natural Language Processing in Machine Translation

Zhaorong Zong, Changchun Hong • International Conference on Mechanical, Control and Computer Engineering (ICMCCE) (2018)

Natural language processing is the core of machine translation. In the history, its development process is almost the same as machine translation, and the two complement each other. This article compares the natural language processing of s...

OPENALEX DOI: https://doi.org/10.1109/icmcce.2018.00112

Deep learning in omics: a survey and guideline

Zhiqiang Zhang, Yi Chen Zhao, Xiangke Liao, Wenqiang Shi et al. • Briefings in Functional Genomics (2018)

Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fo...

OPENALEX DOI: https://doi.org/10.1093/bfgp/ely030

Deep learning for neuroimaging: a validation study

Sergey Plis, Devon Hjelm, Ruslan Salakhutdinov, Elena A. Allen et al. • Frontiers in Neuroscience (2014)

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neu...

OPENALEX cc-by DOI: https://doi.org/10.3389/fnins.2014.00229 PMC: 4138493