A two-stage computational approach for stochastic Darcy-forchheimer non-newtonian flows by Muhammad Shoaib Arif, Muhammad Shoaib Arif, Kamaleldin Abodayeh, Yasir Nawaz

“…The proposed two-stage numerical method integrates a modified time integrator with a second-stage Runge-Kutta scheme, ensuring second-order accuracy in time for deterministic problems. …”
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A Stochastic -Coverage Scheduling Algorithm in Wireless Sensor Networks by Jiguo Yu, Shaohua Ren, Shengli Wan, Dongxiao Yu, Guanghui Wang

“…Coverage is one of the key issues to achieve energy efficiency of a wireless sensor network. Sensor scheduling is one of the most important methods to solve coverage problems. …”
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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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Comparison of Outdoor Radiowave Propagation Models for Land Mobile Systems in the 3.6 GHz and 6 GHz Frequency Bands by Tamás István Unger, Miklós Kuczmann

“…ITU-R P.452-17 emerges as the most reliable and computationally efficient alternative to deterministic methods when terrain effects must be considered without significant computational overhead.…”
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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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A Proposed Stochastic Finite Difference Approach Based on Homogenous Chaos Expansion by O. H. Galal

“…Galerkin projection is used in converting the original stochastic partial differential equation (PDE) into a set of coupled deterministic partial differential equations and then solved using finite difference method. …”
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Research of the effectiveness of equity capital by chemical industry companies during the crisis by O. V. Berezhnaya, E. V. Berezhnaya

“…The purpose of the work is to assess the effectiveness of using their own sources of financing, typical for companies in the chemical industry, during the period of crisis and sanctions restrictions from 2019 to 2022.Materials and methods. Based on traditional methods of statistical analysis, financial analysis and classical deterministic models (in particular, return on equity capital), on the basis of information on the financial results and capital structure of organizations in the SPARK-Interfax system, the authors analyzed the dynamics of equity capital, its components in the chemical industry and its sub-sectors. …”
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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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Building Energy Optimization Using an Improved Exponential Distribution Optimizer Based on Golden Sine Strategy Minimizing Energy Consumption Under Uncertainty by Mohammad Ali Karbasforoushha, Mohammad Khajehzadeh, Suraparb Keawsawasvong, Lapyote Prasittisopin, Thira Jearsiripongkul

“…The conventional Exponential distribution optimizer (EDO) is improved using the Golden sine strategy to boost search process efficiency and reduce the probability of getting trapped in local optima. …”
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RELIABILITY-BASED DESIGN OPTIMIZATION USING OPTIMUM SAFETY FACTORS FOR LARGE-SCALE PROBLEMS by Gh. Kharmanda, I. R. Antypas

“…A numerical application on a large scale problem under  fatigue  loading  shows  the  efficiency of the developed RBDO method relative to the Deterministic Design Optimization (DDO). …”
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Photon number resolution without optical mode multiplication by Vetlugin Anton N., Martinelli Filippo, Dong Shuyu, Soci Cesare

“…Yet, these methods suffer from an inherent trade-off between the efficiency of photon number discrimination and photon detection rate. …”
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Advanced Cooperative Formation Control in Variable-Sweep Wing UAVs via the MADDPG–VSC Algorithm by Zhengyang Cao, Gang Chen

“…The algorithm not only optimizes multi-UAV formation control efficiency but also improves obstacle avoidance, attitude stability, and decision-making speed. …”
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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. …”

Multiscale Sieve for Smart Prime Generation and Application in Info-Security, IoT and Blockchain by Gerardo Iovane, Elmo Benedetto, Carmine Gallo

“…The huge computational cost required to test whether a number is prime and the inefficiency of the known sieving algorithms for extremely large inputs have posed significant challenges in computational number theory. Traditional deterministic prime generation methods struggle to maintain performance when the input sizes increase exponentially. …”
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UAV spatiotemporal crowdsourcing resource allocation based on deep reinforcement learning by Yaxi LIU, Xulong LI, Jiahao HUO, Wei HUANGFU

“…To solve this MDP, we employ the soft actor critic (SAC) algorithm, an advanced deep reinforcement learning method known for its sample efficiency and stability. …”
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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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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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