Cavernas do Mato Grosso do Sul: revisão, atributos condicionantes, análise preditiva e autocorrelação espacial by Alesson Pires Maciel Guirra, Antonio Conceição Paranhos Filho

“…It is not possible to predict by purely deterministic statistical method the occurrence of cavities, being verified stochastic pattern in its distribution. …”
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Geometric thermodynamics of reaction-diffusion systems: Thermodynamic trade-off relations and optimal transport for pattern formation by Ryuna Nagayama, Kohei Yoshimura, Artemy Kolchinsky, Sosuke Ito

“…We also show that a similar geometric method further decomposes the entropy production rate into detailed contributions, e.g., the dissipation from each point in real or wavenumber space. …”
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A robust optimization model for allocation-routing problems under uncertain conditions. by Tingting Zhang, Yanqiu Liu

“…The Trauma Index Score (TIS) method is used to classify casualties into two groups, and the dynamic changes in their injuries after treatment at temporary hospitals are considered. …”
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Probabilistic Forecasting of Provincial Regional Wind Power Considering Spatio-Temporal Features by Gang Li, Chen Lin, Yupeng Li

“…Firstly, the input features are formed through a fused image generation method of geographic and meteorological information as well as a power aggregation strategy, which avoids the extensive and tedious data processing process prior to modeling in the traditional approach. …”
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The L-Curve Criterion as a Model Selection Tool in PLS Regression by Abdelmounaim Kerkri, Jelloul Allal, Zoubir Zarrouk

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Earthquake Decision-Making Tool for Humanitarian Logistics Network: An Application in Popayan, Colombia by Helmer Paz-Orozco, Irineu de Brito Junior, Mario Chong, Yesid Anacona-Mopan, Jhon Alexander Segura Dorado, Mariana Moyano

“…<i>Background</i>: This study presents a comprehensive methodology for enhancing humanitarian logistics planning and management in natural disasters, focusing on earthquakes. <i>Methods</i>: The innovative approach combines a deterministic mathematical model with a simulation model to address the problem from multiple perspectives, aiming to improve efficiency and equity in post-disaster supply distribution. …”
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System of Interconnected Reactor Models of the Sulfur Recovery Unit with Hydrogen Extraction for Hydrogen Energy in a Fuzzy Environment by Batyr Orazbayev, Kulman Orazbayeva, Kanagat Dyussekeyev, Tursinbay Turymbetov, Ramazan Yessirkessinov, Ainur Zhumadillayeva

“…This study proposes a systematic modeling approach that integrates deterministic, statistical, and fuzzy logic methods to enhance process efficiency and accuracy. …”
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Stochastic carbon footprint tracing for power systems with uncertainty by Jiashuo Hu, Mengge Shi, Xiao‐ping Zhang, Youwei Jia

“…Recognizing that the CEF network complexity increases with higher DER penetration, the second method extends the initial approach to enhance computational efficiency while maintaining accuracy, thus ensuring scalability for large‐scale power system topologies. …”
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Decentralizing Coordination in Open Vehicle Fleets for Scalable and Dynamic Task Allocation by Marin Lujak, Stefano Giordani, Andrea Omicini, Sascha Ossowski

“…Self-concerned individually rational vehicle drivers have both local and global objectives, which require coordination using some fair and efficient task allocation method. In this paper, we review the literature on scalable and dynamic task allocation focusing on deterministic and dynamic two-dimensional linear assignment problems. …”
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An Integrated Framework for Infectious Disease Control Using Mathematical Modeling and Deep Learning by Mohammed Salman, Pradeep Kumar Das, Sanjay Kumar Mohanty

“…Precise modeling and prediction methods are essential to develop effective strategies for disease control. …”
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Using Transformers and Reinforcement Learning for the Team Orienteering Problem Under Dynamic Conditions by Antoni Guerrero, Marc Escoto, Majsa Ammouriova, Yangchongyi Men, Angel A. Juan

“…These findings suggest that learning-based methods can offer efficient, scalable, and adaptable solutions for routing problems in dynamic and uncertain environments.…”
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PAPR Reduction in DCO-OFDM Visible Light Communication Systems Using Optimized Odd and Even Sequences Combination by Wei-Wen Hu

“…Even and odd sequences are obtained by adopting an inverse fast Fourier transform on the even and odd parts of a Hermitian symmetry encoded signal, respectively. Furthermore, a deterministic and efficient selection method of cyclic shift and phase rotation is derived to improve PAPR reduction performance and ensure that each candidate is unique, so that the receiver can recover the transmitted candidate signal without the use of SI. …”
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Accelerated Transfer Learning for Cooperative Transportation Formation Change via SDPA-MAPPO (Scaled Dot Product Attention-Multi-Agent Proximal Policy Optimization) by Almira Budiyanto, Keisuke Azetsu, Nobutomo Matsunaga

“…The MADDPG (Multi-Agent Deep Deterministic Policy Gradient) method is popularly used for recognized environments. …”
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A Methodology for Turbine-Level Possible Power Prediction and Uncertainty Estimations Using Farm-Wide Autoregressive Information on High-Frequency Data by Francisco Javier Jara Ávila, Timothy Verstraeten, Pieter Jan Daems, Ann Nowé, Jan Helsen

“…The results demonstrate that the proposed method improves predictive accuracy over the manufacturer’s power curve, achieving a reduction in error measurements of around 1%. …”
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Optimizing resource allocation in industrial IoT with federated machine learning and edge computing integration by Ala'a R. Al-Shamasneh, Faten Khalid Karim, Yu Wang

“…The method also achieved a 40.5% improvement in computational efficiency and a 30-50% reduction in system costs, demonstrating its practicality and scalability. …”
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A Novel Multiobjective Optimization Approach for EV Charging and Vehicle-to-Grid Scheduling Strategy by Muhammad Aurangzeb, Yifei Wang, Sheeraz Iqbal, Md Shafiullah, Sultan Alghamdi, Zahid Ullah

“…These enhancements make our method more effective, flexible, and capable of supporting the transition to a sustainable and efficient energy system.…”
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A Deep Reinforcement Learning Framework for Adaptive Resiliency Enhancement in Smart Power Grids by Boyu Wang, Aliasghar Baziar, Mohammad Reza Askari

“…To overcome these limitations, we propose a deep reinforcement learning framework based on the Deep Deterministic Policy Gradient (DDPG) algorithm, optimized using the Root Mean Square Propagation (RMSprop) method for stable and efficient training. …”
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Co-Optimization of Speed Planning and Energy Management for Plug-In Hybrid Electric Trucks Passing Through Traffic Light Intersections by Xin Liu, Guojing Shi, Changbo Yang, Enyong Xu, Yanmei Meng

“…This model effectively converts the nonlinear constraints related to the position, phase, and timing information of each traffic signal on the road into time-varying constraints, thereby improving computational efficiency. In the lower layer, an energy management model is constructed using the twin delayed deep deterministic policy gradient (TD3) algorithm to achieve optimal allocation of demanded power through the interaction of the TD3 agent with the truck environment. …”
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Local and global sensitivity analysis of key durability parameters of concrete under chloride environment by Lingjie Wu, Chengjian Yu, Fenfei Shi, Xuping Ni

“…By integrating the One-At-a-Time (OAT) method for local sensitivity analysis with the extended Fourier Amplitude Sensitivity Test (EFAST) and Sobol methods for global sensitivity analysis, a systematic evaluation is conducted to identify distinct influence mechanisms of these parameters under deterministic and time-dependent durability life prediction models. …”
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Stochastic Power Control Strategy for Hybrid Electric Propulsion Ships Using Markov Chain-Based Operational Data Augmentation by Su Bin Choi, Soon Ho Hong, Sun Je Kim

“…This strategy resulted in a 3% improvement in efficiency compared to the deterministic method. In addition, it can be implemented in a real-time strategy utilizing stochastic maps.…”
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