Study on User Fraud Identification of PV Expansion Based on a Bottom-Up Approach of a DELM Algorithm Improved by SSA for a Power Distribution Network by Wang Jinpeng, Wei Haojie, Dou Shunyao, Jeremy-Gillbanks, Zhao Xin

“…Next, a Sparrow Search Algorithm (SSA) was applied to optimize the weight parameters of the Deep Extreme Learning Machine (DELM). …”
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Efficient IDS for IoT Networks Using Host-Based Data Aggregation and Multi-Entropy Analysis by Yusei Katsura, Arata Endo, Ismail Arai, Kazutoshi Fujikawa

“…This enables the reduction of computational resources during detection processing while maintaining detection accuracy, even when using fewer features and lightweight machine learning algorithms. The evaluation results demonstrate that the proposed method achieves a maximum reduction of 99.7% (2916 milliseconds) in processing time and 86.4% (633 MiB) in memory usage while maintaining an intrusion detection accuracy of 99.97%, proving its feasibility in constrained environments comparable to IoT gateways.…”
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A Comprehensive Review on Sensor-Based Electronic Nose for Food Quality and Safety by Teodora Sanislav, George D. Mois, Sherali Zeadally, Silviu Folea, Tudor C. Radoni, Ebtesam A. Al-Suhaimi

“…Our review found that most of the efforts use portable, low-cost electronic noses, coupled with pattern recognition algorithms, for evaluating the quality levels in certain well-defined food classes, reaching accuracies exceeding 90% in most cases. …”
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The novel Vogel's approximation method integrated with a random forest algorithm in the vibration analysis of a two-directional functionally graded taper porous beam: Assessment by Ravikiran Chintalapudi, Geetha Narayanan Kannaiyan, Bridjesh Pappula, Seshibe Makgato

“…The material gradation and porosity developed a uniform pattern in the first three modes of fundamental frequencies. …”
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Research on Machine Learning-Based Extraction and Classification of Crop Planting Information in Arid Irrigated Areas Using Sentinel-1 and Sentinel-2 Time-Series Data by Lixiran Yu, Hongfei Tao, Qiao Li, Hong Xie, Yan Xu, Aihemaiti Mahemujiang, Youwei Jiang

“…Additionally, we integrated the vertical–vertical and vertical–horizontal polarization data obtained from synthetic aperture radar (SAR) satellite systems. Machine learning algorithms, including the random forest algorithm (RF), Classification and Regression Trees (CART), and Support Vector Machines (SVM), were employed for planting structure classification. …”
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Developing a molecular diagnostic model for heatstroke-induced coagulopathy: a proteomics and metabolomics approach by Qingbo Zeng, Qingwei Lin, Longping He, Lincui Zhong, Ye Zhou, Xingping Deng, Nianqing Zhang, Qing Song, Qing Song, Jingchun Song, Jingchun Song

“…Functional annotation and pathway enrichment analyses were performed using the GO and KEGG databases, and machine learning models were developed using candidate proteins selected by LASSO and Boruta algorithms to diagnose HSIC. …”
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Predicting and Preventing School Dropout with Business Intelligence: Insights from a Systematic Review by Diana-Margarita Córdova-Esparza, Juan Terven, Julio-Alejandro Romero-González, Karen-Edith Córdova-Esparza, Rocio-Edith López-Martínez, Teresa García-Ramírez, Ricardo Chaparro-Sánchez

“…We collected literature from the Google Scholar and Scopus databases using a comprehensive search strategy, incorporating keywords such as “business intelligence”, “machine learning”, and “big data”. The results highlight a wide range of predictive tools and methodologies, notably data visualization platforms (e.g., Power BI) and algorithms like decision trees, Random Forest, and logistic regression, demonstrating effectiveness in identifying dropout patterns and at-risk students. …”
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Evaluating Ecological Vulnerability and Its Driving Mechanisms in the Dongting Lake Region from a Multi-Method Integrated Perspective: Based on Geodetector and Explainable Machine... by Fuchao Li, Tian Nan, Huang Zhang, Kun Luo, Kui Xiang, Yi Peng

“…Furthermore, the LightGBM algorithm was used for feature optimization, followed by the construction of six machine learning models—Multilayer Perceptron (MLP), Extremely Randomized Trees (ET), Decision Tree (DT), Random Forest (RF), LightGBM, and K-Nearest Neighbors (KNN)—to conduct multi-class classification of ecological vulnerability. …”
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Innovación en sueño by Laura Vigil, Toni Zapata, Andrea Grau, Marta Bonet, Montserrat Montaña, María Piñar

“…However, the integration of artificial intelligence (AI) in sleep medicine has made it possible to automate the analysis of sleep phases and respiratory events with high accuracy.Machine learning algorithms and neural networks have proven to be effective in automatic sleep coding, with hit rates comparable to those of human experts. …”
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Predicting High-Cost Healthcare Utilization Using Machine Learning: A Multi-Service Risk Stratification Analysis in EU-Based Private Group Health Insurance by Eslam Abdelhakim Seyam

“…The research applied three machine learning algorithms, namely logistic regression using elastic net regularization, the random forest, and support vector machines. …”
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Cardiometabolic index predicts cardiovascular events in aging population: a machine learning-based risk prediction framework from a large-scale longitudinal study by Yuanxi Luo, Yuanxi Luo, Zhiyang Yin, Xin Li, Xin Li, Chong Sheng, Ping Zhang, Dongjin Wang, Dongjin Wang, Yunxing Xue

“…For nomogram construction, we utilized an ensemble machine learning framework, combining Boruta algorithm-based feature selection with Random Forest (RF) and XGBoost analyses to determine key predictive parameters.ResultsThroughout the median follow-up duration of 84 months, we documented 1,500 incident CVD cases, comprising 1,148 cardiac events and 488 cerebrovascular events. …”
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Development of a Drought Monitoring System for Winter Wheat in the Huang-Huai-Hai Region, China, Utilizing a Machine Learning–Physical Process Hybrid Model by Qianchuan Mi, Zhiguo Huo, Meixuan Li, Lei Zhang, Rui Kong, Fengyin Zhang, Yi Wang, Yuxin Huo

“…The existing simulation methods like physical process models and machine learning (ML) algorithms have limitations: physical models struggle with parameter acquisition at regional scales, while ML algorithms face difficulties in agricultural settings due to the presence of crops. …”
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Computational Estimation of Football Player Wages by Yaldo L., Shamir L.

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Machine learning identification of a novel vasculogenic mimicry-related signature and FOXM1’s role in promoting vasculogenic mimicry in clear cell renal cell carcinoma by Chao Xu, Sujing Zhang, Jingwei Lv, Yilong Cao, Yao Chen, Hao Sun, Shengtao Dai, Bowei Zhang, Meng Zhu, Yuepeng Liu, Junfei Gu

“…Methods: Consensus clustering identified VRG-associated subtypes. We developed a machine learning framework integrating 12 algorithms to establish a consistent VM-related signature (VRG_score). …”
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Integrating CEUS Imaging Features and LI-RADS Classification for Postoperative Early Recurrence Prediction in Solitary Hepatocellular Carcinoma: A Machine Learning-Based Prognostic... by Liang L, Pang J, Zhang B, Que Q, Gao R, Wu Y, Peng J, Zhang W, Bai X, Wen R, He Y, Yang H

“…Feature selection was performed using univariate Cox regression (p ≤ 0.05), and four ML algorithms—Random Survival Forest (RSF), Gradient Boosting Machine (GBM), CoxBoost, and XGBoost—were applied to develop recurrence prediction models. …”
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Research on feature extraction and intelligent diagnosis method of reciprocating compressor bearing clearance fault by Feng Yan

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Privacy-Aware Detection for Large Language Models Using a Hybrid BiLSTM-HMM Approach by Maryam Abbasalizadeh, Sashank Narain

“…Utilizing the Forward algorithm, our system quantifies privacy risks, enabling users to revise inputs prior to submission and thereby enhancing data privacy. …”
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Using modern clustering techniques for parametric fault diagnostics of turbofan engines by I. J. Buraimah

“…Cluster analysis methods based on Neural Networks such as c-means, k-means, self-organizing maps and DBSCAN algorithm have been used to build clusters. Differences in cluster groupings/patterns between healthy engine and engine with degraded performance are compared and used as the bases for defining faults. …”
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Research on Bearing Fault Diagnosis Method Based on MESO-TCN by Ruibin Gao, Jing Zhu, Yifan Wu, Kaiwen Xiao, Yang Shen

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Beyond Linearity: Uncovering the Complex Spatiotemporal Drivers of New-Type Urbanization and Eco-Environmental Resilience Coupling in China’s Chengdu–Chongqing Economic Circle with... by Caoxin Chen, Shiyi Wang, Meixi Liu, Ke Huang, Qiuyi Guo, Wei Xie, Jiangjun Wan

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