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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Hybrid Optimization Technique for Solving Economic Dispatch Problem: A Case Study of Nigerian Thermal Power System by Gafari Abiola Adepoju, Muniru Olajide Okelola, Muhammed Adekilekun Tijani

“… Economic Dispatch Problem (EDP) is a power system optimization problem that is required to be solved accurately using an efficient optimization technique. Hybrid optimization solutions have provided better optimum results than either deterministic or non-deterministic optimization methods. …”
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Uncertainty-Aware Multimodal Trajectory Prediction via a Single Inference from a Single Model by Ho Suk, Shiho Kim

“…Our approach employs deterministic single forward pass methods, optimizing computational efficiency while retaining robust prediction accuracy. …”
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Leveraging Transfer Learning in Deep Reinforcement Learning for Solving Combinatorial Optimization Problems Under Uncertainty by Fatima Ezzahra Achamrah

“…In recent years, addressing the inherent uncertainties within Combinatorial Optimization Problems (COPs) reveals the limitations of traditional optimization methods. Although these methods are often effective in deterministic settings, they may lack flexibility and adaptability to navigate the uncertain nature of real-world COP/s. …”
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An optimized elliptic curve digital signature strategy for resource-constrained devices by Nawras H. Sabbry, Alla Levina

“…This research addresses these challenges by proposing an optimized ECC digital signature method designed for such environments. The method incorporates two key enhancements: optimizing scalar point multiplication using the cyclic group property of elliptic curve points and the additive inverse property in group theory, and secondly, adopting a deterministic private nonce generation approach, while excluding the public nonce ( $$R$$ ) from the calculation of the challenge to improve signing efficiency. …”
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On the development and analysis of a comprehensive police patrolling model by Fatemeh Mousapour, Rajan Batta, Jose L. Walteros

“…Numerical experiments are conducted to (a) evaluate the computational efficiency of the proposed methods, and (b) explore sensitivity analysis with respect to key parameters. …”
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Energy Management in Microgrids Using Model-Free Deep Reinforcement Learning Approach by Odia A. Talab, Isa Avci

“…MGs offer a flexible and efficient framework for accommodating dispersed energy resources. …”
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Optimizing Accuracy, Recall, Specificity, and Precision Using ILP by Arash Marioriyad, Pouria Ramazi

“…To obtain these measures, the probabilities generated by classifiers must be converted into deterministic labels using a threshold. Exhaustive search methods can be computationally expensive, prompting the need for a more efficient solution. …”
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STRUCTURAL RELIABILITY OPTIMIZATION DESIGN OF REINFORCED SHELL MODEL BASED ON ADAPTIVE SURROGATE MODEL by LIU YuZhuo, CAO LiXiong, WU JianGuo, LI HaiBo

“…Reinforced shell structure is widely used in aerospace load-bearing structures because its high specific stiffness and specific strength.By considering the uncertainty and risk factors in the structural parameters，the Reliability-Based Design Optimization （RBDO） can avoid the overly conservative design of the structure and ensure its reliability and safety.An efficient RBDO method based on adaptive agent model was proposed.This method solves the problem of lightweight design of reinforced shell structure under buckling reliability constraints.The adaptive addition of sample points was implemented through the expected feasibility function criterion，and the discrete variables was continued by constructing piecewise functions.This increases optimization efficiency while ensuring the reliability of design results.Finally，the effectiveness of the proposed method is verified by comparing the RBDO results with the deterministic optimization results.…”
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STRUCTURAL RELIABILITY OPTIMIZATION DESIGN OF REINFORCED SHELL STRUCTURE BASED ON ADAPTIVE SURROGATE MODEL by LIU Yuzhuo, CAO Lixiong, WU Jianguo, LI Haibo

“…Reinforced shell structure is widely used in aerospace load-bearing structures because its high specific stiffness and specific strength.By considering the uncertainty and risk factors in the structural parameters, the reliability-based design optimization (RBDO) can avoid the overly conservative design of the structure and ensure its reliability and safety.An efficient RBDO method based on adaptive surrogate model was proposed to solve the problem of lightweight design of reinforced shell structure under buckling reliability constraints.The adaptive addition of sample points was implemented through the expected feasibility function criterion, and the discrete variables was continued by constructing piecewise functions.This increases optimization efficiency while ensuring the reliability of design results.Finally, the effectiveness of the proposed method is verified by comparing the RBDO results with the deterministic optimization results.…”
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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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Multi-Energy Microgrid Data-Driven Distributionally Robust Optimization Dispatch Considering Uncertainty Correlation by LI Jiawei, SUN Qinghe, WANG Qiong, YE Yujian, HU Heng, ZHANG Xi

“…This transforms the distributionally robust model into a linear deterministic model，thereby enabling an efficient solution using optimization solvers. …”
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THE CONTROLLER OF FUZZY LOGIC IN THE MANAGEMENT OF TECHNOLOGICAL PROCESSES by S. V. Shilkina, E. N. Fokina

“…However, the classical control methods work well only with a completely deterministic control object and deterministic environment, but for fuzzy information systems and highly complex control object, fuzzy control methods are optimal. …”
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A Novel Dynamic Lane-Changing Trajectory Planning Model for Automated Vehicles Based on Reinforcement Learning by Cenxin Yu, Anning Ni, Jing Luo, Jinghui Wang, Chunqin Zhang, Qinqin Chen, Yifeng Tu

“…This study develops a lane-changing model using the deep deterministic policy gradient method, which can simultaneously control the lateral and longitudinal motions of the vehicle. …”
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A novel explicit scheme for stochastic diffusive SIS models with treatment effects by Muhammad Shoaib Arif

“…The scheme is designed as an explicit two-stage method, where only the time-dependent terms are discretized, ensuring computational efficiency. …”
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Rapid Probabilistic Inundation Mapping Using Local Thresholds and Sentinel-1 SAR Data on Google Earth Engine by Jiayong Liang, Desheng Liu, Lihan Feng, Kangning Huang

“…Traditional inundation mapping often relies on deterministic methods that offer only binary outcomes (inundated or not) based on satellite imagery analysis. …”
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Conceptual bases for assessing and modeling sustainable development of a region as an ecological‐socio‐economic system (the example of the Republic of Dagestan) by M. M. Magomedova, U. A.-I. Kurbanova, K. D. Dakhdueva

“…In this regard, the study used methods of quantitative research, which are based on factorial, genetic and normative approaches, including methods of expert assessments, balance planning methods, economic and mathematical methods of optimization and assessment of economic efficiency.Results. …”
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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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MAARS: Multiagent Actor–Critic Approach for Resource Allocation and Network Slicing in Multiaccess Edge Computing by Ducsun Lim, Inwhee Joe

“…Specifically, MAARS utilizes a multiagent deep deterministic policy gradient (MADDPG) for efficient resource distribution in ECS and a soft actor–critic (SAC) technique for robust real-time resource management in ARS. …”
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Fundamental properties and characteristics of flux distribution tallies using proper orthogonal decomposition by Kondo Ryoichi, Yamamoto Akio, Endo Tomohiro

“…This result indicates that the deterministic method might be more efficient for the snapshot calculation. …”
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