Seismic Reliability Analysis of Highway Pile–Plate Structures Considering Dual Stochasticity of Parameters and Excitation via Probability Density Evolution by Liang Huang, Ge Li, Chaowei Du, Yujian Guan, Shizhan Xu, Shuaitao Li

“…Compared to the Monte Carlo method, probability density evolution shows significant advantages in computational accuracy and efficiency for large-scale systems, revealing enhanced discreteness and irregularity under combined randomness. …”
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Optimization research on UAV semantic communication system based on SVD-MADRL by Yibo Yang, Yahe Tan, Liu Liu

“…In addition, compared with traditional algorithms, the semantic communication optimization model constructed in this study performs the best in terms of total reward, data collection efficiency, and accuracy. It has strong stability and convergence ability, with an accuracy close to 1, significantly improving the accuracy and efficiency of unmanned aerial vehicle communication transmission. …”
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A two-stage optimization model for relief logistics and distribution to disaster survivors under two-fold uncertainty by Palash Sahoo

“…The genetic algorithm and particle swarm optimization techniques have been proposed to find the optimal solution for the two deterministic models. The efficiency of our proposed approach is demonstrated with a real-life numerical example.…”
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multi-objective mathematical model for optimizing the collection and recycling of urban waste under conditions of uncertainty(The subject of study : Karaj city) by Mohsen Bijanpoor, Reza Ehtesham Rasi, Davood Gharakhany

“…Since the parameters and information required for designing the waste supply chain network are not always certain, designing the supply chain in a deterministic way decreases its practical efficiency. …”
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Digital Twin and TD3-Enabled Optimization of xEV Energy Management in Vehicle-to-Grid Networks by Irum Saba, Abdulraheem H. Alobaidi, Sultan Alghamdi, Muhammad Tariq

“…This paper addresses these challenges by proposing an advanced ESS framework that integrates digital twin (DT) technology with the twin-delayed deep deterministic policy gradient (TD3) algorithm, a state-of-the-art reinforcement learning method derived from the deep deterministic policy gradient (DDPG). …”
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Comparing variable neighbourhood search algorithms for the direct aperture optimisation in radiotherapy by Mauricio Moyano, Keiny Meza-Vasquez, Gonzalo Tello-Valenzuela, Nicolle Ojeda-Ortega, Carolina Lagos, Guillermo Cabrera-Guerrero

“…The DAO problem seeks to generate a set of deliverable aperture configurations and a corresponding set of radiation intensities. This method accounts for physical and delivery time limitations, facilitating the creation of clinically appropriate treatment programs. …”
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A novel approach to pseudorandom number generation using Hamiltonian conservative chaotic systems by Vinod Patidar, Tanu Singh

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Decentralized Voltage and Var Control of Active Distribution Network Based on Parameter-Sharing Deep Reinforcement Learning by Binqiao Zhang, Changlin He

“…This work introduces a Parameter Sharing - twin-delay deep deterministic policy gradient (PS-TD3) method for carrying out decentralized voltage and var control in active distribution networks. …”
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Tracking Control of CSTRs Based on Improved OU Noise and the TD3 Algorithm by Hongyan Shi, Xiaofei Wu, Guogang Wang

“…To address this challenge, this study proposes a novel deep reinforcement learning (DRL) approach that integrates an improved Ornstein-Uhlenbeck (IOU) noise into the twin delayed deep deterministic policy gradient (TD3) algorithm. This method is applied to the tracking control of continuous stirred tank reactors (CSTRs). …”
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Optimizing Energy Consumption and Latency in IoT Through Edge Computing in Air–Ground Integrated Network With Deep Reinforcement Learning by Vitou That, Kimchheang Chhea, Jung-Ryun Lee

“…Simulation results show that this approach significantly minimizes energy consumption and latency, outperforming conventional optimization methods. Additionally, scalability tests confirm that our framework can efficiently integrate an increasing number of IoT devices and UAVs.…”
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Identification and Valuation of Economic Activities Reserves as a Priorityin Strategic Analysis by Svetlana Evgen’evna Egorova, Natal’ya Nikolaevna Kistaeva

“…Comparative characteristics of the major methods of reserves valuation: method of direct evaluation, method of comparison, deterministic factor analysis, correlation and regression analysis, value analysis, mathematical programming are provided. …”
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MM3: Multimodal framework for regional-scale quantitative landslide risk analysis by William Pollock, Joseph Wartman

“…However, to date, no readily transferable, regional-scale method for PLRA exists. In this work, we expand an existing deterministic multimodal method for landslide risk analysis developed in the country of Lebanon into a linked framework of code-based modules that are location-agnostic and computationally efficient for regional end-to-end risk estimation. • Use of near-global, remote-sensing-based inputs enables risk estimates almost anywhere in the world • Modular computational framework facilitates upgrades of component models as new research becomes available • Probabilistic implementation through a Monte Carlo approach…”
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A comparative approach of analyzing data uncertainty in parameter estimation for a Lumpy Skin Disease model by Edwiga Renald, Miracle Amadi, Heikki Haario, Joram Buza, Jean M. Tchuenche, Verdiana G. Masanja

“…This has driven the interest to research efficient mitigating measures towards controlling the transmission of LSD. …”
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Maximum a posteriori estimation for high-throughput peak fitting in X-ray photoelectron spectroscopy by Tarojiro Matsumura, Naoka Nagamura, Shotaro Akaho, Kenji Nagata, Yasunobu Ando

“…The computation is performed efficiently by the spectrum-adapted expectation–conditional maximisation algorithm with deterministic annealing. …”
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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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A two-stage computational approach for stochastic Darcy-forchheimer non-newtonian flows by Muhammad Shoaib Arif, Muhammad Shoaib Arif, Kamaleldin Abodayeh, Yasir Nawaz

“…This study aims to formulate and validate a computationally efficient two-stage method that accurately captures the effects of non-Newtonian behavior, porous media resistance, and stochastic perturbations. …”
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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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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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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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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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