Implementation of Several Data Mining Strategies on Electronic Nose Data for Identifying Gluten in Cheese by Mohammad Nasiri-Galeh, Mahdi Ghasemi-Varnamkhasti

“…With analyzing 105 Permutations, Finally, the best suitable model to be used for data classification using the Random Forest algorithm and MinMaxScaler for scaling was selected with a prediction accuracy of 99.8% for both test and training datasets.…”
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A Portable UV-LED/RGB Sensor for Real-Time Bacteriological Water Quality Monitoring Using ML-Based MPN Estimation by Andrés Saavedra-Ruiz, Pedro J. Resto-Irizarry

“…The novel combination of ML and MPN analysis was shown to predict in 30 min the bacterial concentration of a water sample with a minimum prediction accuracy of 84%.…”
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Graph-based two-level indicator system construction method for smart city information security risk assessment by Li Yang, Kai Zou, Yuxuan Zou

“…For the simulation of risk level prediction, we compared our method with some machine learning algorithms, such as ridge regression, Lasso regression, support vector regression, decision trees, and multi-layer perceptron. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…Because of the privacy concerns about the transaction data, it is essential not to leak it when training prediction models for credit card fraud analysis. Challenges for credit card fraud monitoring include highly imbalanced datasets and the need for advanced models to detect fraud patterns. …”
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House Value Estimation using Different Regression Machine Learning Techniques by Tarek Ghamrawi, Müesser Nat

“…This study investigates the effectiveness of various regression algorithms in estimating house values using a dataset sourced from Zillow.com, encompassing 15,000 residential properties from Denver, Colorado. …”
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Forecasting the volatility of Financial Time Series by Tree Ensembles by O. S. Vidmant

“…More stringent liquidity and transparency standards in relation to the financial sector also encourage participants to experiment with protective mechanisms and to create predictive algorithms that can not only reduce the losses from the volatility of financial instruments but also benefit from short-term investment manipulations. …”
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Applying Internet information technology combined with deep learning to tourism collaborative recommendation system. by Meng Wang

“…Compared with traditional methods, the proposed algorithm can provide users with personalized travel products more accurately in personalized travel recommendations. …”
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Learning Optimal Dynamic Treatment Regime from Observational Clinical Data through Reinforcement Learning by Seyum Abebe, Irene Poli, Roger D. Jones, Debora Slanzi

“…Our study aims to evaluate the performance and feasibility of such algorithms: tree-based reinforcement learning (T-RL), DTR-Causal Tree (DTR-CT), DTR-Causal Forest (DTR-CF), stochastic tree-based reinforcement learning (SL-RL), and Q-learning with Random Forest. …”
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Temporal-Sequence Offline Reinforcement Learning for Transition Control of a Novel Tilt-Wing Unmanned Aerial Vehicle by Shiji Jin, Wenjie Zhao

“…Although online reinforcement learning algorithms offer adaptability, they depend on real-world exploration, posing considerable safety and cost risks for safety-critical UAV applications. …”
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Detection and Tracking of Environmental Sensing System for Construction Machinery Autonomous Operation Application by Junyi Chen, Qipeng Cai, Xinhai Hu, Qihuai Chen, Tianliang Lin, Haoling Ren

“…By taking the environmental characteristics and operating conditions of construction machinery into consideration, a set of environmental sensing algorithms based on LiDAR for construction machinery scenarios is studied. …”
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Machine Learning Enhances Soil Aggregate Stability Mapping for Effective Land Management in a Semi-Arid Region by Pegah Khosravani, Ali Akbar Moosavi, Majid Baghernejad, Ndiye M. Kebonye, Seyed Roohollah Mousavi, Thomas Scholten

“…Machine learning algorithms coupled with environmental and soil covariates were used. …”
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A framework based on mechanistic modelling and machine learning for soil moisture estimation by Sabri Kanzari, Sana Ben Mariem, Samir Ghannem, Safouane Mouelhi, Hiba Ghazouani, Bechir Ben Nouna

“…These values were used as inputs to the Hydrus 1D model to generate soil water content profiles over a 27-year period. 109 profiles were calculated using machine learning algorithms (regression trees; random forest; support vector machine) to predict soil moisture content from daily values of rainfall and evaporation. …”
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Latest Trend and Challenges in Machine Learning– and Deep Learning–Based Computational Techniques in Poultry Health and Disease Management: A Review by Shwetha V., Maddodi B. S., Vijaya Laxmi, Abhinav Kumar, Sakshi Shrivastava

“…The advancement of machine learning (ML)– and deep learning (DL)–based algorithms are boons for poultry health and disease management. …”
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Impact of Airborne Radio Occultation Observations on Short Term Precipitation Forecasts of an Atmospheric River by Phuong‐Nghi Do, Jennifer S. Haase, Ivette Hernández Baños, Pawel Hordyniec, Bing Cao

“…This study evaluates the impact of assimilating ARO bending angle observations using the Model for Prediction Across Scales—Atmosphere—Joint Effort for Data assimilation Integration (MPAS‐JEDI). …”
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Phonon-mediated high-temperature superconductivity in clathrate superhydride ThCeH18 under pressure by Prutthipong Tsuppayakorn-aek, Wei Luo, Thiti Bovornratanaraks

“…Abstract Predicting high-temperature superconductivity in hydrogen-rich dense metallic states under pressure remains a significant challenge. …”
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Functional control of the technical condition method for aircraft control system sensors under complete parametric uncertainty by J. V. Bondarenko, E. Yu. Zybin

“…Fast tuning, fast response and selective sensitivity of the developed algorithms are noted.…”
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Measuring the Dimension Accuracy of Products Created by 3D Printing Technology with the Designed Measuring System by Martin Pollák, Dominik Sabol, Karol Goryl

“…Comprehensive analysis of measurements in combination with advanced algorithms can provide more accurate dimensional characteristics and the prediction of defects. …”
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Intelligent resource allocation in internet of things using random forest and clustering techniques by Nahideh Derakhshanfard, Lida Hosseinzadeh, Fahimeh Rashid Jafari, Ali Ghaffari

“…A Random Forest model is then trained to accurately predict the resource needs of each cluster, enabling optimal allocation. …”
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Artificial intelligence in spinal deformity by Joash Suryavanshi, David Foley, Michael H. McCarthy

“…Background: Artificial intelligence (AI) refers to algorithms that utilize data to mimic human cognition. …”
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Anti‐interference lithium‐ion battery intelligent perception for thermal fault detection and localization by Luyu Tian, Chaoyu Dong, Rui Wang, Yunfei Mu, Hongjie Jia

“…After denoising by the autoencoder, the prediction results improved by 22% compared to non‐local mean denoising and by about 32% compared to noisy images.…”
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