A Novel Hybrid Deep Learning Framework for Evaluating Field Evapotranspiration Considering the Impact of Soil Salinity by Yao Rong, Weishu Wang, Peijin Wu, Pu Wang, Chenglong Zhang, Chaozi Wang, Zailin Huo

“…Specifically, we integrated physical constraints from process models (Penman‐Monteith or Shuttleworth‐Wallace) and salinity‐induced stomatal stress mechanisms into the DL algorithm, and evaluated its performance by comparing four diverse scenarios. …”
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Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany by Loukas Kyriakidis, Rushit Kansara, Maria Isabel Roldán Serrano

“…To solve the resulting nonlinear and constrained optimization problem at each RHA iteration, we propose a novel hybrid algorithm that combines Bayesian optimization (BO) with the Interior Point OPTimizer (IPOPT). …”
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Drilling Condition Identification Method for Imbalanced Datasets by Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang

“…Additionally, classification loss values were reduced by 0.32, 0.3315, 0.2893, and 0.2246, respectively. …”
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Selection and Identification of a Model of Elasto-Viscoplasticity of the Filled Fluorocomposite according to Free and Constrained Compression Tests by D. S. Petukhov, A. A. Adamov, I. E. Keller

“…Tests for constrained compression were performed for two values of the strain rate, and for free compression – for three values of the strain rate in the range of 10-6 – 10-3 s-1. …”
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Cooperative and Hierarchical Optimization Design of Shipboard MVDC System for Adapting to Large, Pulsed Power Load by Zhimeng Liu, Yongbao Liu, Youhong Yu, Rui Yang

“…Supplying power to large, pulsed power loads in shipboard medium voltage direct current integrated power systems is challenging due to the limited dynamic power responsiveness of the gas turbine. …”
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TradeWise: Towards Context-Aware Stock Market Predictions with Sentiment and Political Insights by Andreas Marpaung, David Masterson

“…Our novel approach suggests that sentiment and political insights, when processed and integrated effectively, offer substantial predictive value that could refine the accuracy of financial prediction models. …”
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Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…For example, a transition service adapted to the stage of illness (like the First episode and Rapid Early intervention for Eating Disorders (FREED) model of outpatient care) may be of value. Furthermore, flexible integration between the range of services and community support is essential to cover and respond to the variable range of needs in this patient group. …”
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Machine learning-driven nanoparticle toxicity by Zied Hosni, Sofiene Achour, Fatma Saadi, Yangfan Chen, Mohammed Al Qaraghuli

“…The integration of Shapley Additive exPlanations (SHAP) values provided an interpretative insight into the predictive models, allowing for a quantitative assessment of feature impact. …”
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Neuro-fuzzy inference system and white shark optimization of coagulation-flocculation of aquaculture wastewater treatment by A.F. Mohamed, H. Rezk

“…Therefore, the objective of this study is determining the optimal operating condition of coagulation-flocculation through optimizing the values of the three input parameters.METHODS: Artificial intelligence and recent optimzation algorithms are integrated to achieve the purpose of this study work. …”
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Nonuniformity Correction Method of Infrared Detector Based on Statistical Properties by Li Dandan, Ding Xiang, Chai Mengyang, Ma Chao, Sun Dexin

“…First, the pixel points of all images are reordered according to their pixel values to provide a uniform reorganisation data. Then, the linear correlated region based on the recombined data is extracted using a judgment algorithm that processes the linear correlations of multiple regions to simulate the detector's response curve and find the nonuniformity correction coefficient of each pixel. …”
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Photoprotective activity from Colombian Caribbean brown algae using HPLC-DAD metabolic profiling by MCR-ALS data analysis by Sara P. Abril, Natalia Rincón-Díaz, Mónica Puyana, Leonardo Castellanos, Freddy A. Ramos

“…These findings were correlated with the HPLC-DAD metabolic profile using the Multivariate Curve Resolution- Alternating Least Squares (MCR-ALS) algorithm and multivariate data analysis tools. Extracts from Canistrocarpus cervicornis (CCe) and Stypopodium zonale (SS) presented the most promising photoprotective activity. …”
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Hedge-Algebra-Based Phase-Locked Loop for Distorted Utility Conditions by Dinko Vukadinović, Tien Duy Nguyen, Cat Ho Nguyen, Nhu Lan Vu, Mateo Bašić, Ivan Grgić

“…Optimized fuzziness parameters and linguistic rule base of the HAC are obtained by a genetic algorithm using the integral of absolute error as the performance index during optimization. …”
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Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement by D. Neudecker, T. E. Cutler, M. Devlin, P. Brain, N. Gibson, M. J. Grosskopf, M. W. Herman, J. Hutchinson, T. Kawano, A. Khatiwada, N. Kleedtke, E. Leal-Cidoncha, R. C. Little, A. E. Lovell, A. Stamatopoulos, E. C. Thompson, S. A. Vander Wiel, E. Williamson

“…They are contrasted to application-driven, integral, data where one or few resulting values inform a broad set of nuclear data across several nuclides and energies. …”
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Machine learning‐based model for worsening heart failure risk in Chinese chronic heart failure patients by Ziyi Sun, Zihan Wang, Zhangjun Yun, Xiaoning Sun, Jianguo Lin, Xiaoxiao Zhang, Qingqing Wang, Jinlong Duan, Li Huang, Lin Li, Kuiwu Yao

“…The best models were identified by integrating nine ML algorithms and interpreted using SHAP, and to develop a final risk calculation tool. …”
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Dynamic Virtual Simulation with Real-Time Haptic Feedback for Robotic Internal Mammary Artery Harvesting by Shuo Wang, Tong Ren, Nan Cheng, Rong Wang, Li Zhang

“…Our key innovations include a topology-preserving cutting algorithm, a bidirectional tissue coupling mechanism, and dual-channel haptic feedback for electrocautery simulation. …”
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Lifetime Prediction Analysis of Proton Exchange Membrane Fuel Cells Based on Empirical Mode Decomposition—Temporal Convolutional Network by Chao Zheng, Changqing Du, Jiaming Zhang, Yiming Zhang, Jun Shen, Jiaxin Huang

“…This study proposes a novel EMD-TCN-GN algorithm, which, for the first time, integrates empirical mode decomposition (EMD), temporal convolutional network (TCN), and group normalization (GN) by using EMD to adaptively decompose non-stationary signals (such as voltage fluctuations), the dilated convolution of TCN to capture long-term dependencies, and combining GN to group-calibrate intrinsic mode function (IMF) features to solve the problems of modal aliasing and training instability. …”
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A hybrid data-driven method for voltage state prediction and fault warning of Li-ion batteries by Yufeng Huang, Xuejian Gong, Zhiyu Lin, Lei Xu

“…Secondly, a Bi-LSTM module is used to learn long-term dependence relationships among fused features while integrating a self-attention mechanism. To further verify the algorithm's effectiveness, a new 18650 battery dataset has been set up under various conditions between day and night. …”
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The PLSR-ML fusion strategy for high-accuracy leaf potassium inversion in karst region of Southwest China by Zhihao Song, Zhihao Song, Wen He, Yuefeng Yao, Ling Yu, Jinjun Huang, Yong Xu, Haoyu Wang

“…Validation coefficient of determination (R²) values reached 0.89, 0.94, and 0.96, respectively—representing improvements of 206%, 147%, and 108% over standalone algorithms. …”
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Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning by Qianli Si, Shoichi Matsuda, Yasunobu Ando, Toshiyuki Momma, Yoshitaka Tateyama

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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…However, satellite-derived AOD datasets frequently suffer from missing values due to factors such as cloud cover, algorithmic limitations, and various atmospheric conditions. …”
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