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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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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The L-Curve Criterion as a Model Selection Tool in PLS Regression by Abdelmounaim Kerkri, Jelloul Allal, Zoubir Zarrouk

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Distributed Robust Low-Carbon Economic Dispatch of Power Systems Considering Extreme Scenarios by HU Heng, QIN Jianru, LI Haibo, LIU Jiefeng

“…Particularly， tail risks triggered by extreme weather and the dynamic mismatches between stochastic RE fluctuations and conventional unit regulation rates invalidate conventional deterministic scheduling models reliant on typical scenarios. …”
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Incorporating Risk in Operational Water Resources Management: Probabilistic Forecasting, Scenario Generation, and Optimal Control by Ties van derHeijden, Miguel Angel Mendoza‐Lugo, Peter Palensky, Nick van deGiesen, Edo Abraham

“…Recognizing the limitations of deterministic methods in the face of weather, energy system, and market uncertainties, we propose a scalable stochastic Model Predictive Control (MPC) framework that integrates probabilistic forecasting, scenario generation, and stochastic optimal control. …”
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Flexible Load Stochastic Optimal Control of Wind Power-Based Hydrogen Production and Ammonia Synthesis Systems Based on the Itô Process by Guoshan YANG, Jie ZHU, Wenqin SONG, Yiwei QIU, Buxiang ZHOU

“…Then, the stochastic optimization problem is transformed into a deterministic second-order cone programming by the trajectory sensitivity decomposition and solved by the stochastic model predictive control (SMPC) in a rolling-horizon manner, avoiding the disadvantages of high computational complexity and low efficiency of the traditional sampling-based stochastic control methods. …”
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Quantum reinforcement learning in continuous action space by Shaojun Wu, Shan Jin, Dingding Wen, Donghong Han, Xiaoting Wang

“…To overcome this limitation, we introduce a quantum Deep Deterministic Policy Gradient (DDPG) algorithm that efficiently addresses both classical and quantum sequential decision problems in continuous action spaces. …”
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Risk–Cost Equilibrium for Grid Reinforcement Under High Renewable Penetration: A Bi-Level Optimization Framework with GAN-Driven Scenario Learning by Feng Liang, Ying Mu, Dashun Guan, Dongliang Zhang, Wenliang Yin

“…Moreover, the stress investment frontier exhibits clear convexity, enabling planners to identify cost-efficient resilience strategies. Spatial congestion maps and scenario risk-density plots further illustrate the ability of adversarial learning to reveal latent structural bottlenecks not captured by conventional methods. …”
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Advanced predictive machine and deep learning models for round-ended CFST column by Feng Shen, Ishan Jha, Haytham F. Isleem, Walaa J.K. Almoghayer, Mohammad Khishe, Mohamed Kamel Elshaarawy

“…Comparison with 10 analytical models demonstrates that these traditional methods, though deterministic, struggle to capture the nonlinear interactions inherent in CFST columns, thus yielding lower accuracy and higher variability. …”
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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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SENSITIVITY OF THE TECHNICAL CONDITION OF ELECTRICAL EQUIPMENT OF MOBILE ROBOTIC COMPLEXES FOR SOLVING MONITORING TASKS by A.V. Zayara, M.E. Danilin

“…To solve the problem of sensing the technical condition of the electrical equipment of mobile robotic complexes through the integration of sensory information, a monitoring procedure is proposed as an integral part of a maintenance and repair system based on a proactive concept. Materials and methods. Using the method of associative analogy, a comparison of the time-deterministic process of reducing the performance of the robotics complex with a deterioration in human performance has been carried out, which makes it possible to assess the technical condition according to a generalized parameter characterizing the energy efficiency of the RTK using fuzzy logical inference. …”

Measuring Component Importance for Network System Using Cellular Automata by Li He, Qiyan Cao, Fengjun Shang

“…This paper concentrates on the component importance measure of a network whose arc failure rates are not deterministic and imprecise ones. Conventionally, a computing method of component importance and a measure method of reliability stability are proposed. …”
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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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Recognition of the finger vascular system using multi‐wavelength imaging by Tomasz Moroń, Krzysztof Bernacki, Jerzy Fiołka, Jia Peng, Adam Popowicz

“…Analyses of data from over 100 volunteers, using five different deterministic methods for feature extraction, consistently demonstrated improved identification efficiency with the addition of data obtained from another wavelength. …”
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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

“…Wind farm performance monitoring has traditionally relied on deterministic models, such as power curves or machine learning approaches, which often fail to account for farm-wide behavior and the uncertainty quantification necessary for the reliable detection of underperformance. …”
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Cost-effectiveness analysis of the multi-strategy WHO emergency care toolkit in regional referral hospitals in Uganda. by Kalin Werner, Nicholas Risko, Joseph Kalanzi, Lee A Wallis, Teri A Reynolds

“…Parameter uncertainty was assessed using both deterministic and probabilistic sensitivity analyses. …”
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Analyzing execution path non-determinism of the Linux kernel in different scenarios by Yucong Chen, Xianzhi Tang, Shuaixin Xu, Fangfang Zhu, Qingguo Zhou, Tien-Hsiung Weng

“…However, the execution path of a system call is effectively non-deterministic in Linux kernel space, which challenges the test coverage-based verification recommended by the functional safety standards. …”
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Online Resource Allocation and Trajectory Optimization of STAR–RIS–Assisted UAV–MEC System by Xi Hu, Hongchao Zhao, Wujie Zhang, Dongyang He

“…Since the proposed problem is a long–term stochastic optimization problem, we use the Lyapunov method to transform it into three deterministic online optimization subproblems and iteratively solve them alternately. …”
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Blockchain oracles for decentralized agricultural insurance using trusted IoT data by Manoj T, Krishnamoorthi Makkithaya, Narendra V. G., Vijaya Murari T

“…However, blockchain operates as a deterministic and synchronized state system, which means it cannot directly access real-world data for decentralized applications. …”
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3D geological modeling technology of medium-deep geothermal field in Shenshui 501 geothermal field in Damintun Sag by CONG Shufei, ZHOU Hong, ZHAO Yan, JIN Hailong, LIU Peng, WU Rongbi, CHEN Yuanchun

“…This is achieved by combining various types of data and employing both deterministic and stochastic modeling techniques, thereby establishing a robust method for thermal reservoir geological modeling using Petrel. …”
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