Intelligent data-driven system for mold manufacturing using reinforcement learning and knowledge graph personalized optimization for customized production by Chengcai He, Jiaxing Deng, Jingchun Wu, Beicheng Qin, Jinxiang Chen, Yan Li, Qiangsheng Huang

“…The proposed system integrates knowledge graphs with intelligent algorithms to support the development of a smart quality control framework tailored to personalized manufacturing. …”
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Machine Learning-Assisted Sustainable Mix Design of Waste Glass Powder Concrete with Strength–Cost–CO₂ Emissions Trade-Offs by Yuzhuo Zhang, Jiale Peng, Zi Wang, Meng Xi, Jinlong Liu, Lei Xu

“…Subsequently, a MOO framework minimized unit cost and CO₂ emissions while meeting compressive strength targets (15–70 MPa), solved using the NSGA-II algorithm for Pareto solutions and TOPSIS for decision-making. …”
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The spatial extent and the dispersal strategy of species shape the occupancy frequency distribution of stream insect assemblages by I. Szivák, Z. Csabai, D. Schmera, A. Móra

“…Applying a computer program algorithm, we produced samples with different spatial extent. …”
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Data-driven causal behaviour modelling from trajectory data: A case for fare incentives in public transport by Yuanyuan Wu, Alex Markham, Leizhen Wang, Liam Solus, Zhenliang Ma

“…Causal discovery phase uses Peter-Clark (PC) algorithm to learn a directed acyclic graph that captures the causal relationships among variables. …”
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Consideration of corona discharge in relation to operational dispatch control of power system mode 500 kV by V. A. Menshov, A. V. Valiansky, T. I. Khairullin

“…It is also important to take into account dynamic corona discharge for system operated by automatic algorithms in order to avoid occurrence of incorrect interpretations of phase shifts caused by weather changes as potentially dangerous electrical processes caused by regime processes of a possible transition of the system to a pre-emergency state.…”
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Complete Electric Field Characterization of Ultrashort Multicolor Pulses by Maximilian Kubullek, Miguel A. Silva-Toledo, Roland E. Mainz, Fabian Scheiba, Rafael de Q. Garcia, Felix Ritzkowsky, Giulio Maria Rossi, Franz X. Kärtner

“…The method relies on the measurement of the perturbative third-order nonlinear response generated in a noble gas target while varying the delay between 2 pulses. The resulting spectrograms can be reconstructed using a custom evolutionary algorithm. …”
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Exploring the Possibilities of Implementing the ALS-Based 3-30-300 Concept for Urban Green Space Management in Small Municipalities by Krzysztof Mitelsztedt, Mariusz Ciesielski, Tomasz Hycza, Marek Lisańczuk, Kacper Guderski, Sylwia Kurpiewska, Krzysztof Korzeniewski

“…The method proposed in this study shows that the tree visibility component of the 3-30-300 concept is the most fluctuating index, and it strongly depends on the settings of the algorithm parameter, as well as on the placement of artificially generated observers. …”
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Enhanced Inverse Model Predictive Control for EV Chargers: Solution for DC–DC Side by Abdullah Berkay Bayindir, Ali Sharida, Sertac Bayhan, Haitham Abu-Rub

“…IMPC, a recently introduced control method for power electronic converters, leverages the strengths of model predictive control (MPC), while minimizing its computational burden. IMPC excels in managing sophisticated and nonlinear systems, controlling multiple objectives, and adhering to various constraints. …”
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Identifying where and when urban renewal occurs: a continuous change detection-based framework using two decades’ worth of Landsat data by Chong Liu, Qi Zhang, Huabing Huang, Hanzeyu Xu, Xiao Cheng

“…Urban renewal plays a central role in enhancing city liveability by rebuilding outdated structures into productive and vibrant spaces. While satellite remote sensing enables physical characterization of urban environments, identifying the precise location and timing of renewal remains challenging. …”
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Design of Constant Speed Controller for Hydraulic Retarder Based on Robust Control by Pengxiang Song, Ao Meng, Yang Ding

“…In order to verify the effectiveness of the algorithm, three different operating conditions were set according to the vehicle mass and road gradient, and simulation tests were carried out in the MATLAB/Simulink environment. …”
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The future of precision orthopaedics: personalized data-driven practice by Deiary F. Kader, Andrew Coppola, Aditya Vijay, Andreas Fontalis, Fares S. Haddad

“…However, challenges related to data quality, algorithm transparency, ethical considerations, and infrastructure development must be addressed to ensure robust and equitable implementation. …”
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IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition by Mashael Maashi, Huda G. Iskandar, Mohammed Rizwanullah

“…Finally, the attraction-repulsion optimization algorithm (AROA) adjusts the hyperparameter values of the CNN-BiGRU-A method optimally, resulting in more excellent classification performance. …”
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Fault Kinematics of the 2022 Delingha Mw 5.6 and Mw 5.7 Earthquakes Revealed by InSAR Observations by Xuening Wang, Donglin Wu, Lian Liu, Chenglong Li, Yongliang Bai, Xing Huang

“…We then utilized a Bayesian inversion algorithm to delineate the fault geometries of the two events, and further resolved their coseismic fault slip. …”
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Joint Lagrangian Relaxation and Dynamic Programming Approach for a Multi-Period Multi-Product Location-Inventory Problem by Claudio Araya-Sassi, German Paredes-Belmar, Gabriel Gutierrez-Jarpa, Ricardo Gatica Escobar

“…We propose a Lagrangian relaxation algorithm and the subgradient approach as a solution method. …”
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Distributionally robust multi-stage stochastic programming for mid- and long-term cross-regional power markets by Yuhan Huang, Tao Ding, Xiaosheng Zhang, Shuhai Feng, Yiding Jin, Yangsheng Sun, Tong Xing

“…To overcome the premature convergence problem in conventional methods, a distributionally robust stochastic dual dynamic programming algorithm is proposed to give an exact upper bound. …”
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Spatiotemporal distribution and influencing factors of Chinese marine protected areas under a social-ecological system framework by Mingbao Chen, Mingbao Chen, Mingbao Chen, Zhibin Xu, Yuhao Wang

“…It also developed a mathematically based algorithm to locate thresholds where effects change.ResultsResults show GDP over ¥55 billion (1998-based, equal to ¥106.5 billion in 2020) to be conducive to MPA establishment, while built-up areas over 63 km² are antagonistic to MPA development. …”
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An in-depth exploration of supervised and semi-supervised learning on face recognition by Purnawansyah, Wibawa Aji Prasetya, Widiyaningtyas Triyanna, Haviluddin, Darwis Herdianti, Azis Huzain

“…This study aims to assess the effectiveness of various algorithms in the realms of supervised and semi-supervised learning applied to three multiclass facial image datasets: JAFFE, Georgia tech, and Yale. …”
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The impact of environmental variables on reed stands of the intermittent Lake Cerknica, Slovenia: 40 years of change by Nik Ojdanič, Alenka Gaberščik, Igor Zelnik, Aleksandra Golob

“…Decision tree-based data mining using the M5P algorithm effectively identified significant changes in MSAVI2. …”
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Improvement of Positive and Negative Feedback Power Hardware-in-the-Loop Interfaces Using Smith Predictor by Lucas Braun, Jonathan Mader, Michael Suriyah, Thomas Leibfried

“…Therefore, an interface algorithm (IA) must be chosen. The ideal transformer method (ITM) and the partial circuit duplication (PCD) are popular IAs, where a distinction is made between voltage- (V-) and current-type (C-) IAs. …”
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Investigating the Nonlinear Relationship Between the Built Environment and Urban Vitality Based on Multi-Source Data and Interpretable Machine Learning by Wenhao Liu, Zhen Yang, Chen Gui, Gen Li, Hongyi Xu

“…In this study, we investigate the potential non-linear interactions between the built environment and urban vitality by employing an interpretable spatial machine learning framework that integrates the XGBoost model with the SHapley Additive exPlanations (SHAP) algorithm. Additionally, we analyze the determinants of urban vitality across both micro and macro-scales using multi-source data, semantic segmentation models, and street view imagery. …”
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