Analyzing Blockchain Consensus Mechanisms for Internet of Things Networks by Maxim Melnikov, Elena Igonina

Get full text

Random Oversampling-Based Diabetes Classification via Machine Learning Algorithms by G. R. Ashisha, X. Anitha Mary, E. Grace Mary Kanaga, J. Andrew, R. Jennifer Eunice

“…The proposed approach considers ML algorithms such as random forest, gradient boosting models, light gradient boosting classifiers, and decision trees, as they are widely used classification algorithms for diabetes prediction. …”
Get full text

Neural Network VS Genetic and Particle Swarm Optimization Algorithms in Bankruptcy by Alireza Azarberahman

“…The evidence reveals the effectiveness of the metaheuristic algorithms compared to linear ones in predicting bankruptcy. …”
Get full text

Atmospheric Modeling for Wildfire Prediction by Fathima Nuzla Ismail, Brendon J. Woodford, Sherlock A. Licorish

“…Our study focuses on developing wildfire prediction models using one-class classification algorithms. …”
Get full text

Genomic selection in pig breeding: comparative analysis of machine learning algorithms by Ruilin Su, Jingbo Lv, Yahui Xue, Sheng Jiang, Lei Zhou, Li Jiang, Junyan Tan, Zhencai Shen, Ping Zhong, Jianfeng Liu

Get full text

Melanoma risk prediction models by Nikolić Jelena, Lončar-Turukalo Tatjana, Sladojević Srđan, Marinković Marija, Janjić Zlata

“…The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. …”
Get full text

The malaria secretome: from algorithms to essential function in blood stage infection. by Christiaan van Ooij, Pamela Tamez, Souvik Bhattacharjee, N Luisa Hiller, Travis Harrison, Konstantinos Liolios, Taco Kooij, Jai Ramesar, Bharath Balu, John Adams, Andrew P Waters, Chris J Janse, Kasturi Haldar

Get full text

Optimization based machine learning algorithms for software reliability growth models by Myeongguen Shin, Juwon Jung, Jihyun Lee, Insoo Ryu, Sanggun Park

“…However, many previous studies have relied on single optimization methods or deep learning approaches, which are prone to local optima and extrapolation issues, reducing prediction accuracy. To fill this gap, current study employs a broader range of optimization algorithms based on the Least Squares Method (LSM) and Maximum Likelihood Estimation (MLE) to approximate global optima. …”
Get full text

Machine Learning Models to Predict Google Stock Prices by Cosmina Elena Bucura, Paolo Giudici

Get full text

Automated Input Variable Selection for Analog Methods Using Genetic Algorithms by P. Horton, O. Martius, S. L. Grimm

“…Previous work showed the potential of genetic algorithms (GAs) to optimize most of the AM parameters. …”
Get full text

A hybrid BOA-SVR approach for predicting aerobic organic and nitrogen removal in a gas-liquid-solid circulating fluidized bed bioreactor by Shaikh Abdur Razzak, Nahid Sultana, S.M. Zakir Hossain, Muhammad Muhitur Rahman, Yue Yuan, Mohammad Mozahar Hossain, Jesse Zhu

“…This study introduces the hybrid of the Bayesian optimization algorithm and support vector regression (BOA-SVR) models to predict the removal of aerobic organic (total chemical oxygen demand, COD) and nitrogen compounds such as total Kjeldahl Nitrogen (TKN), ammonium nitrogen (NH4-N), and nitrate nitrogen (NO3-N) from municipal wastewater in a gas-liquid-solid circulating fluidized bed (GLSCFB) bioreactor. …”
Get full text

Optimizing Renewable Energy Integration Using IoT and Machine Learning Algorithms by Orken Mamyrbayev, Ainur Akhmediyarova, Dina Oralbekova, Janna Alimkulova, Zhibek Alibiyeva

“…Results showed significant improvements in forecasting accuracy, with the LSTM model achieving a 59.1% reduction in Mean Absolute Percentage Error compared to the persistence model. …”
Get full text

Plantar pressure classification and feature extraction based on multiple fusion algorithms by Xiaotian Bai, Xiao Hou, Yiling Song, Zhengyan Tang, Hongfeng Huo, Jingmin Liu

Get full text

Logatom articulation index evaluation of speech enhanced by blind source separation and single-channel noise reduction by Szymon DRGAS, Jędrzej KOCIŃSKI, Aleksander P. SĘK

Get full text

Enhancing power transformer health assessment through dimensional reduction and ensemble approaches in Dissolved Gas Analysis by Abdelmoumene Hechifa, Saurabh Dutta, Abdelaziz Lakehal, Hazlee Azil Illias, Arnaud Nanfak, Chouaib Labiod

Get full text

An Exploratory Application of Machine Learning Algorithms in Estimating Net Salaries in Romania by Adriana Aiftincăi

“…The results demonstrate a high prediction accuracy (MAE: 59.47 lei, RMSE: 97.60 lei – Random Forest model), providing realistic values for future salary scenarios. …”
Get full text

Scattering-Based Machine Learning Algorithms for Momentum Estimation in Muon Tomography by Florian Bury, Maxime Lagrange

“…Several real-life requirements are considered, such as the inclusion of hit reconstruction efficiency and resolution and the need for a momentum resolution prediction that can improve reconstruction methods.…”
Get full text

Comparison of algorithms using deep reinforcement learning for optimization of hyperbolic metamaterials by Kenta Hamada, Hui-Hsin Hsiao, Wakana Kubo

“…By analyzing the absorption spectra obtained from the three algorithms with limited number of datasets, we assessed the prediction accuracy of each algorithm. …”
Get full text

TRENDS IN SPANISH LITERATURE. HOW NEW TECHNOLOGIES INFLUENCE THE PROCESS OF LITERARY CREATION by Alina-Viorela PRELIPCEAN

Get full text

PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems by Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, Huiting ZHOU, Hong LUO

“…Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model, a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed, and a system model of fusion technology was designed.Through simulation comparison with other literature methods, it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability, but the algorithm implementation complexity was too high.Therefore, a complementary SLM-Clipping fusion solution was proposed, and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method, the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system, and greatly improves the computational efficiency.…”
Get full text