Research on the connectivity reliability analysis and optimization of natural gas pipeline network based on topology by Xiuxuan Yang, Kun Chen, Minghui Liu

“…This study proposes an integrated framework combining connectivity reliability evaluation with adaptive topology optimization. First, a minimum path set-based reliability model is developed, leveraging an enhanced depth-first search (DFS) algorithm for efficient path identification and binary decision diagrams (BDD) to eliminate 92% of redundant terms in reliability formulas, reducing computational complexity by 40% compared to Monte Carlo simulations. …”
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Slope deformation prediction based on GA–BP neural networks by Wenhui TAN, Kai LI, Huimin LIU, Meifeng CAI, Qifeng GUO

“…To enhance the BP neural network performance and prevent it from falling into local minima, a genetic algorithm (GA) is introduced to the training step of the BP neural network. …”
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Research on prediction of bottom hole flowing pressure for vertical coalbed methane wells based on improved SSA-BPNN by YU Yang, DONG Yintao, LI Yunbo, BAO Yu, ZHANG Lixia, SUN Hao

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Construction and Application of Feature Recommendation Model for Remote Sensing Interpretation of Rock Strata Based on Knowledge Graph by Liufeng Tao, Qirui Wu, Miao Tian, Zhong Xie, Jianguo Chen, Yueyu Wu, Qinjun Qiu

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Rice seed integrity evaluation: Developing a rapid onsite system to check seed fraud using a portable NIR spectroscopic device coupled with smartphone technology by Ernest Teye, Charles Lloyd Yeboah Amuah, Vida Gyimah Boadu, Kwadwo Anokye Dompreh, Maxwell Darko Asante, Francis Padi Lamptey, Stephen Narh, Daniel Dzorkpe Gamenyah, George Oduro Nkansah, Selorm Akaba

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An optimized support vector machine for lung cancer classification system by Mayowa O. Oyediran, Olufemi S. Ojo, Ibrahim A. Raji, Abidemi Emmanuel Adeniyi, Oluwasegun Julius Aroba, Oluwasegun Julius Aroba

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FlowSeries: flow analysis on financial networks by Arthur Capozzi, Salvatore Vilella, Dario Moncalvo, Marco Fornasiero, Valeria Ricci, Silvia Ronchiadin, Giancarlo Ruffo

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Fault Detection System of Photovoltaic Based on Artificial Neural Network by Ali Salman Zamzeer, Mansour S. Farhan, Haider TH. ALRikabi

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Construction of a risk prediction model for pulmonary infection in patients with spontaneous intracerebral hemorrhage during the recovery phase based on machine learning by Jixiang Xu, Yuan Li, Fumin Zhu, Fumin Zhu, Xiaoxiao Han, Liang Chen, Yinliang Qi, Yinliang Qi, Xiaomei Zhou, Xiaomei Zhou

“…Seven ML algorithms were employed to build predictive models, with performance evaluated based on the area under the receiver operating characteristic (AUC) curve, sensitivity, specificity, and accuracy. …”
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Resource-Efficient Personalization in Federated Learning With Closed-Form Classifiers by Eros Fani, Raffaello Camoriano, Barbara Caputo, Marco Ciccone

“…Furthermore, we propose Only Local Labels (<monospace>OLL</monospace>), a novel PFL technique that simplifies local classifiers by focusing only on locally relevant classes, preventing misclassifications and improving efficiency. Our empirical evaluation on real-world cross-device datasets shows that <monospace>Fed3R</monospace>, combined with <monospace>OLL</monospace>, significantly improves performance and reduces training costs in heterogeneous FL and PFL scenarios.…”
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Solar Irradiance Prediction Method for PV Power Supply System of Mobile Sprinkler Machine Using WOA-XGBoost Model by Dan Li, Jiwei Qu, Delan Zhu, Zheyu Qin

“…The prediction accuracy and stability of the proposed method are then evaluated for different input parameters through training and testing. …”
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Heuristic based federated learning with adaptive hyperparameter tuning for households energy prediction by Liana Toderean, Mihai Daian, Tudor Cioara, Ionut Anghel, Vasilis Michalakopoulos, Efstathios Sarantinopoulos, Elissaios Sarmas

“…The evaluation results demonstrate a significant improvement in average prediction accuracy and better capturing of energy patterns compared to the federated averaging approach. …”
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Exploring Multi-Pathology Brain Segmentation: From Volume-Based to Component-Based Deep Learning Analysis by Ioannis Stathopoulos, Roman Stoklasa, Maria Anthi Kouri, Georgios Velonakis, Efstratios Karavasilis, Efstathios Efstathopoulos, Luigi Serio

“…In this work, we focus on the analysis of the segmentation results of a pre-trained U-net model trained and validated on brain MRI examinations containing four different pathologies: Tumors, Strokes, Multiple Sclerosis (MS), and White Matter Hyperintensities (WMH). …”
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Adaptive Blind Stokes-Space Based Equalizer for RSOP in SV-DD Systems With High Chromatic Dispersion Tolerance by Yu Jin, Di Li, Pin Yi, Mengfan Cheng, Songnian Fu, Ming Tang, Deming Liu, Lei Deng

“…In our simulation, the conventional Stokes space-based method and the training sequences (TS) method are both evaluated for comparison. …”
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A machine learning based prediction model for short term efficacy of nasopharyngeal carcinoma by Qiulu Zhong, Xiangde Li, Qinghua Du, Qianfu Liang, Danjing Luo, Jiaying Wen, Haiying Yue, Wenqi Liu, Xiaodong Zhu, Jian Li

“…RSF model constructed by machine-learning algorithm based on radiological dosimetric parameters and clinical characteristics can better predict the short-term efficacy of LANPC, and is an effective tool to evaluate the short-term efficacy of different LANPC patients during treatment.…”
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Visceral obesity anthropometric indicators as predictors of acute pancreatitis severity by Kaier Gu, Wenxuan Shang, Dingzhou Wang

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Research on early warning model of coal spontaneous combustion based on interpretability by Huimin Zhao, Xu Zhou, Jingjing Han, Yixuan Liu, Zhe Liu, Shishuo Wang

“…The dataset was then divided into the training and test sets in a 7:3 ratio, and the extracted indicators of each gas were used as inputs to the model and the temperature was used as outputs. …”
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Prediction of hydrogen production in proton exchange membrane water electrolysis via neural networks by Muhammad Tawalbeh, Ibrahim Shomope, Amani Al-Othman, Hussam Alshraideh

“…A novel approach is introduced by employing the Levenberg–Marquardt backpropagation (LMBP) algorithm for training the ANN. This model is designed to predict HPR based on critical operational parameters, including anode and cathode areas (mm2), cell voltage (V) and current (A), water flow rate (mL/min), power (W), and temperature (K). …”
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Deep Learning-Based Recurrence Prediction in HER2-Low Breast Cancer: Comparison of MRI-Alone, Clinicopathologic-Alone, and Combined Models by Seoyun Choi, Youngmi Lee, Minwoo Lee, Jung Hee Byon, Eun Jung Choi

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Segmentation versus detection: Development and evaluation of deep learning models for prostate imaging reporting and data system lesions localisation on Bi‐parametric prostate magn... by Zhe Min, Fernando J. Bianco, Qianye Yang, Wen Yan, Ziyi Shen, David Cohen, Rachael Rodell, Dean C. Barratt, Yipeng Hu

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