Assessment model of ozone pollution based on SHAP-IPSO-CNN and its application by Xiaolei Zhou, Xingyue Wang, Ruifeng Guo

“…Firstly, an atmospheric dispersion model is utilized to predict the distribution concentration of VOCs emitted by enterprises in the park at the target monitoring stations based on the ozone generation mechanism. …”
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Leveraging ensemble learning-based stock preselection with multiobjective investment optimization for stepwise decision-supported portfolio management by Jui-Sheng Chou, Tran-Bao-Quyen Pham

“…In the first phase, the FBI-XGB model predicts company profitability, selecting candidates with higher expected returns. …”
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A Simple Method for Correcting Empirical Model Densities During Geomagnetic Storms Using Satellite Orbit Data by Daniel A. Brandt, Charles D. Bussy‐Virat, Aaron J. Ridley

“…Underestimation of the density during these conditions translates to errors in orbit propagation that reduce the accuracy of any resulting orbit predictions. These drawbacks risk the safety of astronauts and orbiting spacecraft and also limit understanding of the physics of thermospheric density enhancements. …”
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Model-Based Detection of Coordinated Attacks (DCA) in Distribution Systems by Nitasha Sahani, Chen-Ching Liu

“…The developed learning algorithm identifies the most probable attack path to reach the attacker’s objective by predicting the next attack steps. …”
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Continuous and Unconstrained Tremor Monitoring in Parkinson’s Disease Using Supervised Machine Learning and Wearable Sensors by Fernando Rodriguez, Philipp Krauss, Jonas Kluckert, Franziska Ryser, Lennart Stieglitz, Christian Baumann, Roger Gassert, Lukas Imbach, Oliver Bichsel

“…Based on features extracted from the sensor data, a Support Vector Machine was trained to predict tremor severity. Due to the inherent imbalance in tremor scores, we applied dataset rebalancing techniques. …”
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Study on Finite Element Model Modification of Long-Span Suspension Bridge Based on BPANN-GA by Zi-Xiu Qin, Xi-Rui Wang, Wen-Jie Liu, Zi-Jian Fan

“…The trained neural network is then used to predict the natural frequencies corresponding to different modal shapes under various parameters. …”
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Development of a Low-Cost Sensor System for Accurate Soil Assessment and Biological Activity Profiling by Antonio Ruiz-Gonzalez, Harriet Kempson, Jim Haseloff

“…The algorithm could predict seed germination rates with high accuracy (RSMLE = 0.01, and R² = 0.99), enabling an objective and non-invasive study of the impact of multiple environmental parameters in soil quality. …”
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Mathematical Modeling of Tuberculosis Transmission Dynamics With Reinfection and Optimal Control by Francis Oketch Ochieng

“…Existing TB models often neglect seasonal variations, optimal control, and reinfection, limiting their accuracy in predicting disease dynamics. This study presents a novel data‐driven SVEITRS mathematical model incorporating these factors to analyze TB transmission dynamics. …”
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A Hybrid Approach for the Container Loading Problem for Enhancing the Dynamic Stability Representation by Ana María Montes-Franco, Juan Camilo Martinez-Franco, Alejandra Tabares, David Álvarez-Martínez

“…The mechanical model dynamically analyzes the forces and accelerations acting on the cargo to predict loss of support, overturning, or critical velocity deltas that would damage it. …”
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Fuzzy control system of multioperational machine status by Andrey K. Tugengold, Andrey I. Izyumov, Roman N. Voloshin, Mikhail Y. Solomykin

“…Materials and Methods. A new algorithm for constructing an expert system based on the fuzzy logic methods is proposed. …”
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Methodology for Estimating the Cost of Construction Equipment Based on the Analysis of Important Characteristics Using Machine Learning Methods by Nataliya Boyko, Oleksii Lukash

“…The practical significance of this work lies in developing an algorithm for predicting the cost of heavy machinery by assessing several parameters.…”
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Identification of ferroptosis-related gene signatures in temporal lobe epilepsy with hippocampal sclerosis by Fan Gao, Jinzi Li

“…We used weighed gene co-expression network analysis (WGCNA) algorithm, single-factor logistic regression analysis, and LASSO algorithm to screen characteristic FR-DEGs. …”
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Rate-Adaptive LiDAR Point Cloud Streaming Over LEO Satellite Networks by Dominic Laniewski, Nils Aschenbruck

“…We develop a novel, real-time capable rate-adaptation algorithm leveraging Google Draco. It predicts optimal encoding parameters for each mini point cloud to maximize the point cloud quality under varying network conditions. …”
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Possibilities of magnet-resonance tomography usage while examining patients with reccurent genital prolapse by Banakhevych R.M.

“…Reducing the distance while performing Valsalva samples from cervical pubo-coccygeal line 2-3 cm was seen as second-best result of the operation – 26,7%, questionable form of recurrence was observed in 15,6% of patients. The developed algorithm makes it possible to determine the extent of the procedure and to predict possible intraoperative complications and results of operations, to avoid changes of operation plan, to minimize the risk of recurrence and the need for re-surgery. …”
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IDENTIFICATION OF NOMINAL DYNAMIC CHARACTERISTICS OF AIRCRAFT GAS TEMPERATURE SENSORS by A. F. Sabitov, I. A. Safina

“…The developed method makes it possible to predict the dynamic performance of the specific types of gas temperature sensors in the expected operating conditions.…”
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Short-Term Power Load Forecasting Using Adaptive Mode Decomposition and Improved Least Squares Support Vector Machine by Wenjie Guo, Jie Liu, Jun Ma, Zheng Lan

“…Then, the ILSSVM is presented to predict different power load components, separately. …”
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Simulación del vaciado continuo de perfiles de aceros al carbono de baja aleación//Simulation of the continuous casting of low carbon steel profiles by Yusdel Díaz-Hernández, Alberto Fiol-Zulueta, José Arzola-Ruiz

“…The most outstanding characteristic of the model was the inclusion of complex processes of heat interchange, metal phase changes, distribution of temperatures in the mould, chemical composition of the metal, flow of water in the primary and<br />secondary cooling system and the casting speed. Moreover, the algorithm permitted to predict the behaviour of the process variables in the continuous casting of steel according to its profile and type.…”
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Linking dietary fiber to human malady through cumulative profiling of microbiota disturbance by Xin Zhang, Huan Liu, Yu Li, Yanlong Wen, Tianxin Xu, Chen Chen, Shuxia Hao, Jielun Hu, Shaoping Nie, Fei Gao, Gengjie Jia

“…By leveraging microbiota disturbance similarities, we (1) classified 32 types of dietary fibers into six functional subgroups, revealing correlations with fiber solubility; (2) established associations among 161 diseases, uncovering shared microbiota disturbance patterns that explain disease co‐occurrence (e.g., type II diabetes and kidney diseases) and distinct microbiota patterns that discern symptomatically similar diseases (e.g., inflammatory bowel disease and irritable bowel syndrome); (3) designed a body‐site‐specific microbiota disturbance scoring scheme, computing a disturbance score (DS) for each disease and highlighting the pronounced capacity of Crohn's disease to disturb gut microbiota (DS = 14.01) in contrast with food allergy's minimal capacity (DS = 0.74); (4) identified 1659 fiber‐disease associations, predicting the potential of dietary fiber to modulate specific microbiota changes associated with diseases of interest; (5) established murine models of inflammatory bowel disease to validate the preventive and therapeutic effects of arabinoxylan that notably perturbed the Bacteroidetes and Firmicutes phyla, as well as the Bacteroidetes and Lactobacillus genera, aligning with our model predictions. …”
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A Statistical Approach in Designing an RF-Based Human Crowd Density Estimation System by S. Y. Fadhlullah, Widad Ismail

“…A signal path loss propagation model was also proposed to assist in predicting the human crowd density. The human crowd properties verified by using the statistical approach may offer a new side of understanding and estimating the human crowd density.…”
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The dual-edged potential of AI autonomously defining loss functions by Abbas Ghori

“…Abstract A loss function is one of the key components considered in machine learning as they steer the model toward the optimal performance by quantifying the discrepancy between the predicted outcome and the actual outcome. They predominantly act as guiding principles for any optimization algorithm, thereby influencing both the convergence characteristics as well as the generalization of the model. …”
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