Research on Fusion of Locomotive Safety Monitoring and Detection Data and Its Application by GONG Li, QIAO Bin, ZHAO Chao, YAO Kai

“…To solve the problems of long cycle, high cost and low efficiency of traditional maintenance methods, a method of equipment quality diagnosis, evaluation and prediction based on decision tree algorithm is put forward to build an intelligent maintenance system. …”
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Exploring qubit-ADAPT-VQE for materials discovery in direct air capture by Marco Antonio Barroca, Rodrigo Neumann Barros Ferreira, Mathias Steiner

“…Quantum computing can potentially accelerate the discovery of solid sorbents for DAC by predicting molecular binding energies. In this work, we explore algorithms for predicting gas adsorption in metal–organic frameworks using a quantum computer. …”
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An improved model accuracy for forecasting risk measures: application of ensemble methods by Katleho Makatjane, Kesaobaka Mmelesi

“…Statistical-based predictions with extreme value theory improve the performance of the risk model not by choosing the model structure that is expected to predict the best but by developing a model whose results are a combination of models with different shapes. …”
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Quantum Neural Networks Approach for Water Discharge Forecast by Liu Zhen, Alina Bărbulescu

“…The lower error between the recorded values and the predicted ones in the evaluation of maxima compared to the case of the competitors mentioned shows that the algorithm best fits the extremes. …”
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A systematic review of machine learning approaches in cochlear implant outcomes by Anu Prasad Sreenivasan Nair, Srikanta K. Mishra, Pedro Andres Alba Diaz

“…Imaging-based studies demonstrated high predictive accuracy for language and speech perception outcomes. …”
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Service quality evaluation of integrated health and social care for older Chinese adults in residential settings based on factor analysis and machine learning by Zhihan Liu, Caini Ouyang, Nian Gu, Jiaheng Zhang, Xiaojiao He, Qiuping Feng, Chunguyu Chang

“…Comparative indices such as Mean Squared Error, Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and predictive performance metrics were employed to assess the models. …”
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基于序列二次规划理论传动系统中的非对称式盘式制动器制动尖叫研究 by 鲍莉, 王俊峰, 刘振刚

“…In order to study the brake squeal of transmission disc brake,the asymmetric disk brake cooling channel concept is introduced,by SQP optimization algorithm the relevant constraints is established,the asymmetric cooling channel geometry data obtained by the optimization theory is intraduced into the brake squeal prediction model,the relevant characteristics variation rule is analyzed and the relevant model is established to verify the results. …”
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Reliability Evaluation of Cryogenic Shut-Off Valve Based on Weibull Segmented Model by Yi Lu, Jian-Ming Zheng, Ting Chen

“…In order to improve the prediction accuracy of cryogenic shut-off valve failures and quantitatively analyze the distribution law of cryogenic shut-off valve failures, this study establishes a solution model based on genetic algorithm and statistics of cryogenic shut-off valve operating data, which is combined with two Weibull segmented models. …”
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Collaborative carbon emission peak actions in urban agglomerations: multi-agent reinforcement learning analysis of the urban agglomerations of Beijing-Tianjin-Hebei and Yangtze Riv... by Bingbing Zhao, Min Deng, Wei-Zhen Lu, Kaiqi Chen

“…Coordinating carbon emission reduction strategies across cities helps mitigate the growth of carbon emissions and promote the achievement of carbon peaking and carbon neutrality goals. …”
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A two-layer low-carbon economic planning method for park-level integrated energy systems with carbon-energy synergistic hub by Yunfei Mu, Haochen Guo, Zhijun Wu, Hongjie Jia, Xiaolong Jin, Yan Qi

“…From a dual “carbon-energy” perspective, it enhances investment effectiveness and carbon reduction sensitivity by deeply exploring the energy conservation and carbon reduction potential of PIES.…”
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INTERGENIC INTERACTIONS OF TUMOR NECROSIS FACTOR ALPHA, INTERLEUKIN 17, AND OSTEOPROTEGERIN IN THE IMMUNOPATHOGENESIS OF RHEUMATOID ARTHRITIS IN THE RUSSIAN POPULATION OF THE CHELY... by Yulia Chumacheva, Daria Stashkevich, Tatiana Suslova, Daria Shmelkova, Aleksandra Burmistrova

“…To analyse the data we applied the multifactor dimensionality reduction (MDR) algorithm, which constructs predictive case–control models and evaluates their robustness through ten-fold cross-validation and permutation testing.The algorithm identified three most informative combinations comprising four to six SNPs each; every combination showed statistical significance and high predictive accuracy. …”
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Modeling and validation of wearable sensor-based gait parameters in Parkinson’s disease patients with cognitive impairment by Guo Hong, Guo Hong, Fengju Mao, Fengju Mao, Mingming Zhang, Fei Zhang, Fei Zhang, Xiangcheng Wang, Kang Ren, Kang Ren, Zhonglue Chen, Zhonglue Chen, Xiaoguang Luo, Xiaoguang Luo

“…The logistic regression model demonstrated superior predictive performance (test set AUC: 0.957), outperforming other machine learning algorithms. …”
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Development and retrospective validation of an artificial intelligence system for diagnostic assessment of prostate biopsies: study protocol by Martin Eklund, Brett Delahunt, Lars Egevad, Hemamali Samaratunga, Mattias Rantalainen, Marcello Gambacorta, Einar Gudlaugsson, Bodil Ginnerup Pedersen, Xiaoyi Ji, Karina Dalsgaard Sørensen, Kelvin Szolnoky, Nita Mulliqi, Anders Blilie, Henrik Olsson, Matteo Titus, Geraldine Martinez Gonzalez, Sol Erika Boman, Masi Valkonen, Svein Reidar Kjosavik, José Asenjo, Paolo Libretti, Marcin Braun, Radzislaw Kordek, Roman Łowicki, Kristina Hotakainen, Päivi Väre, Benedicte Parm Ulhøi, Pekka Ruusuvuori, Toyonori Tsuzuki, Emilius Adrianus Maria Janssen, Kimmo Kartasalo

“…Digital pathology and artificial intelligence (AI) algorithms for analysing whole slide images show promise in improving the accuracy and efficiency of histopathological assessments. …”
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Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

“…Three key innovations drive this research: (1) A dynamic PSO algorithm incorporating adaptive learning factors and nonlinear inertia weight for precise RBF parameter optimization; (2) A hierarchical feature processing strategy combining mutual information selection with correlation-based dimensionality reduction; (3) Adaptive model architecture adjustment for small-sample scenarios. …”
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Application of the Lagrange Equation for Intelligent Sensor Vibration Control for Power Network Monitoring by Xiaojing Cheng

“…Then, the control effect of the TMDI system is studied by numerical analysis, and the vibration reduction effect of the TMDI system and the tuned mass damper (TMD) system is compared. …”
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Sensitivity analysis of factors influencing the curve negotiation performance of hot metal train by TIAN Mingjie, HUANG Zhihui, CHEN Xuejing, YANG Quan, YU Hongda

“…A sensitivity analysis of factors affecting the performance of hot metal trains negotiating curves was carried out by using the gradient algorithm. The results show that, under 26 different operating conditions, the derailment coefficient of the 6 hot metal cars exhibits a consistent trend with the wheel load reduction rate, with the maximum derailment coefficient observed for the first car being most significant. …”
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Adaptive Modulation Tracking for High-Precision Time-Delay Estimation in Multipath HF Channels by Qiwei Ji, Huabing Wu

“…Simulation results based on the Watterson channel model demonstrate that MATE achieves an average time-delay estimation error of approximately 0.01 ms with a standard deviation of approximately 0.01 ms, representing a 94.12% reduction in mean error and a 96.43% reduction in standard deviation compared to the traditional Generalized Cross-Correlation (GCC) method. …”
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Enhancing Renewable Energy Hosting Capacity in Unbalanced Microgrids via Empowering Smart Inverters by Hossam H. H. Mousa, Karar Mahmoud, Matti Lehtonen

“…The results demonstrate significant improvements, including a 16% reduction in feeder congestion, a 150% increase in PV penetration, a 13% reduction in power losses, and decreased reliance on the UG, ensuring enhanced power quality and system reliability.…”
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Determination of metallization degree of pre-reduced chromite with image and rietveld analysis by Leino T., Taskinen P., Eric R.H.

“…Metallization degrees for the investigated samples ranged from 15 to 65 % depending on the extent of reduction which was a function of time, reduction temperature, and methane content of the gas mixture. …”
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Optimisation of Integrated Heat Pump and Thermal Energy Storage Systems in Active Buildings for Community Heat Decarbonisation by Zaid Al-Atari, Rob Shipman, Mark Gillott

“…The study employs an algorithm that adjusts thermal storage charging and discharging cycles to align with off-peak periods. …”
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