Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

“…This study developed an advanced bankruptcy prediction model using Support Vector Machines (SVM), Random Forest (RF), and Artificial Neural Network (ANN) algorithms based on datasets from the UCI machine learning repository. …”
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Fast, smart, and adaptive: using machine learning to optimize mental health assessment and monitor change over time by Daiana Colledani, Claudio Barbaranelli, Pasquale Anselmi

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Multiobjective optimization of dielectric, thermal, and mechanical properties of inorganic glasses utilizing explainable machine learning and genetic algorithm by Jincheng Qin, Faqiang Zhang, Mingsheng Ma, Yongxiang Li, Zhifu Liu

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Investigating the Optimal Flow Rate for Hydroponic Plants Using IoT and the Decision Tree Model by Tapanee Treeratanaporn, Thongchai Phairoh

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A Big Data Based Analytical Model for Telecom Operator's Energy Usage Optimization by Ai Fang, Duo Jin, Xiong Xu, Bing Liang

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Optimizing a Machine Learning Algorithm by a Novel Metaheuristic Approach: A Case Study in Forecasting by Bahadır Gülsün, Muhammed Resul Aydin

“…This study introduces a novel hybrid approach that combines the artificial bee colony (ABC) and fire hawk optimizer (FHO) algorithms, specifically designed to enhance hyperparameter optimization in machine learning-based forecasting models. …”
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Structural strength analysis and optimization of converter lug based on Kriging model by HE Guanqiang, LIU Yongjiang, LI Hua, CHEN Liming

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The Application Based on Support Vector Machine Optimized by Particle Swarm Optimization and Genetic Algorithm by MAN Chun-tao, LIU Bo, CAO Yong-cheng

“…In order to improve the precision of the parameter optimization, the research integrates the Particle Swarm Optimization Algorithm with Support Vector Machine, and matches the experimental data, and then establishes a steadystate model of complex process system, which is based on Particle Swarm Optimization Algorithm and Support Vector Machine On the basis of this model, an improved Particle Swarm Optimization Algorithm introduced to Genetic Algorithm is proposed, in order to overcome the defects of Particle Swarm. …”
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Grape vine (Vitis vinifera) yield prediction using optimized weighted ensemble machine learning approach by Nobin Chandra Paul, Pratapsingh S. Khapte, Navyasree Ponnaganti, Sushil S. Changan, Sangram B. Chavan, K. Ravi Kumar, Dhananjay D. Nangare, K. Sammi Reddy

“…With increasing demand for high-quality grapes, both for domestic consumption and export, there is a pressing need to improve yield prediction models for better resource management. In this study, we propose an optimized weighted ensemble machine learning approach for predicting grape vine yield, integrating multiple morphological, physiological, and berry quality parameters. …”
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Machining effects and multi-objective optimization in Inconel 718 turning with unitary and hybrid nanofluids under MQL by Paresh Kulkarni, Satish Chinchanikar

“…Designing tooling and cooling systems to prevent cutting tool damage is crucial while machining difficult-to-cut nickel alloys. This study investigates the machining effects during turning Inconel 718 using unitary aluminum oxide (Al2O3) and hybrid aluminum oxide+multi-walled carbon nanotube type (Al2O3+MWCNT) nanofluids under minimum quantity lubrication (NFMQL) through mathematical modeling and multi-objective optimization. …”
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Recent Progress in Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes by Sheng Du, Zixin Huang, Li Jin, Xiongbo Wan

Subjects: “…data-driven modeling…”
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Integrating Machine Learning-Based Remaining Useful Life Predictions with Cost-Optimal Block Replacement for Industrial Maintenance by Young-Suk Choo, Seung-Jun Shin

“…The approach integrates machine learning for RUL prediction, Weibull distribution for reliability analysis, and a block replacement model with minimal repair to optimize preventive maintenance. …”
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Harnessing Machine Learning for Diabetes Prediction: Optimizing Classifiers to Tackle Canada's Growing Health Challenge by Mark Gerald Anastacio, Alam Md Twariqul

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Tunnel water inflow prediction using explainable machine learning and augmented partially missing dataset by Shengdong Ju, Guangzhao Ou, Tao Peng, Yanning Wang, Quanlin Song, Peng Guan

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Bayesian optimization and machine learning for vaccine formulation development. by Lillian Li, Sung-In Back, Jian Ma, Yawen Guo, Thomas Galeandro-Diamant, Didier Clénet

“…Stepwise analysis and model optimization demonstrated progressive improvements of model quality and prediction accuracy. …”
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A novel machine learning approach for portfolio optimization by Saman Haratizadeh, Fatemeh Rezaee

“…At the end based on the predicted return of the numerous random portfolios, the appropriate weight for each asset is selected.Findings: Comparing the returns of adjusted portfolios with this model and adjusted portfolios with other portfolio optimization methods shows the superiority of the proposed model.Originality/Value: In this paper, by using machine learning models, the process of selecting the appropriate stock of the portfolio and allocating capital among the candidate stocks is done optimally.…”
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Design and parameter optimization of portable tree transplanting machine by Zhang Jingping, Zhu Jianxi, Sun Teng

“…Second, in order to increase the machine's working performance, a response surface method was considered to optimize the working parameter of the portable tree transplanting machine. …”
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Enhancing Neural Network Training Through Neuroevolutionary Models: A Hybrid Approach to Classification Optimization by Hyasseliny A. Hurtado-Mora, Luis A. Herrera-Barajas, Luis J. González-del-Ángel, Roberto Pichardo-Ramírez, Alejandro H. García-Ruiz, Katea E. Lira-García

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A predictive analytics approach with Bayesian-optimized gentle boosting ensemble models for diabetes diagnosis by Behnaz Motamedi, Balázs Villányi

“…Effective disease management necessitates the accurate and timely prediction of lung cancer and diabetes. Machine learning (ML) based models have garnered attention in the realm of predictive healthcare, with ensemble methods, in particular, bolstering algorithms to improve classification performance. …”
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A Novel Prediction Model for the Sales Cycle of Second-Hand Houses Based on the Hybrid Kernel Extreme Learning Machine Optimized Using the Improved Crested Porcupine Optimizer by Bo Yu, Deng Yan, Han Wu, Junwu Wang, Siyu Chen

“…For this reason, this paper develops a prediction model of the second-hand housing sales cycle based on the hybrid kernel extreme learning machine (HKELM) optimized using the Improved Crested Porcupine Optimizer (CPO), which has achieved rapid and accurate prediction. …”
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