A Novel Search Algorithm and Scan Time Estimation in Airborne Ground Penetrating Radar Using Cell Footprint Meshing by Morteza Kazerooni, Ehsan Shahroosvand

“…Simulation results indicate that this deterministic, geometry-based method yields an approximate 24% reduction in search time, consequently minimizing resource utilization. …”
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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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Microsphere-assisted generation of localized optical emitters in 2D hexagonal boron nitride by Yang Xiliang, Shin Dong Hoon, Watanabe Kenji, Taniguchi Takashi, Steeneken Peter G., Caneva Sabina

“…Our microsphere-assisted defect generation method reduces the emission area by a factor of 5 and increases the fluorescence collection efficiency by approximately 10 times compared to microsphere-free samples. …”
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User-cooperative dynamic resource allocation for backscatter-aided wireless-powered MEC network by Huaiwen He, Chenghao Zhou, Feng Huang, Hong Shen, Yihong Yang, Shangsong Liang, Xinyuan Jin

“…By leveraging Dinkelbach’s method and stochastic network optimization technique, we transform the problem into a series of deterministic sub-problems for each time slot, and convert the non-convex sub-problem into convex ones. …”
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Wind speed prediction for trains on bridges using enhanced variational mode decomposition assisted feature extraction and physical auxiliary mechanism by Zhilan Zhu, Yuan Jiang, Haicui Wang, Shuoyu Liu

“…Hence, the proposed method stands as a viable and efficient alternative for forecasting the short-term wind speed.…”
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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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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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Influence of Precast Member Corbels on Seismic Performance of Precast Beam-Slab-Column Joints by Hongtao Liu, Pengchao Kong, Taoping Ye

“…To improve the construction efficiency of precast structures, reinforced concrete corbels acted as support members are the most common connection method. …”
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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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Data-driven identification and analysis of passenger riding paths in megacity metro system by Lianghui Xie, Zhenji Zhang, Robin Qiu, Daqing Gong

“…Design/methodology/approach – The authors develop a method to leverage certain passengers’ deterministic riding paths to corroborate other passengers’ uncertain paths. …”
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Multi-objective optimization of residential energy-saving design based on fuzzy multi-criteria decision-making behavior model by Suzhen Pei, Gaoxiang Chen, Jian Yao, Yichen Dang

“…Compared to a deterministic baseline model assuming fixed occupant behavior, the proposed method achieves an 8.95 % reduction in per-unit-area energy consumption (from 32.5 to 29.6 kWh/m2), a 63 % decrease in inter-unit energy differences (from 510 to 189 kWh), and a marginal increase of about 2 % in annual discomfort hours (from 286 to 292 h). …”
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Resilience driven EV coordination in multiple microgrids using distributed deep reinforcement learning by Yuxin Wu, Ting Cai, Xiaoli Li

“…Then, the coordination problem of each EV is formulated as a partially observable Markov decision process, and an attention-based distributed multi-agent deep deterministic policy gradient method, namely AD-MADDPG, is proposed to learn the optimal strategies. …”
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A POSSIBILISTIC APPROACH TO CALCULATING THE INTERNAL RATE OF RETURN FOR INVESTMENT PROJECTS WITH FUZZY CASH FLOWS by E. S. Volkova, V. B. Gisin

“…We believe the proposed method can be applied to evaluating the efficiency of investment projects with fuzzy cash flows.…”
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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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Human-AI in affordance perspective: a study on ChatGPT users in the context of Indonesian users by Rizca Haqqu, Alya Rahma Zahrani, Astri Wulandari, Firdaus Azwar Ersyad, Adrio Kusmareza Adim

“…Using a qualitative descriptive method with light netnographic observation, this study examines user interactions and discussions within online communities. …”
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A Wide-Range TCSC Based ADN in Mountainous Areas Considering Hydropower-Photovoltaic-ESS Complementarity by Yao Guo, Shaorong Wang, Dezhi Chen

“…The simulation results demonstrate the effectiveness of the proposed method.…”
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Unmanned Surface Vessel Cluster Path Planning Based on Deep Reinforcement Learning by Manjiang YU, Jiawei HE, Bowen XING

“…Firstly, a long and short-term memory module was introduced based on the multi-agent deep deterministic policy gradient algorithm to enhance the ability of the USVs to utilize the temporal information in path planning; secondly, a multi-level representational experience pool was designed to improve the training efficiency and data utilization and reduce the interference between different experiences; finally, stochastic network distillation was used as a curiosity mechanism to provide intrinsic rewards for the USVs to explore new regions and solve the convergence due to the sparse rewards. …”
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Analysis of Meeting Early Childhood Education Resource Needs Through Monte Carlo Simulation by Citra Aulia Uzliva, Philips Ratu Bunga, Yenik Wahyuningsih

“…These findings highlight that the approach offers more flexible and realistic estimates than conventional deterministic methods. Therefore, ECE administrators are encouraged to integrate quantitative methods such as Monte Carlo Simulation into their operational planning to enhance efficiency, resilience to student population dynamics, and data-driven decision-making. …”
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STOCHASTIC APPROACH FOR EVALUATION OF RELIABILITY AND RESIDUAL LIFE OF TRANSPORT STRUCTURES by U. N. Rabtsau

“…In order to ensure maximum efficiency of investments in operation of transport network it is necessary exactly evaluate reliability and residual life of structures. …”
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Federated Reinforcement Learning-Based Dynamic Resource Allocation and Task Scheduling in Edge for IoT Applications by Saroj Mali, Feng Zeng, Deepak Adhikari, Inam Ullah, Mahmoud Ahmad Al-Khasawneh, Osama Alfarraj, Fahad Alblehai

“…This corroborates that the proposed method can preserve privacy by handling issues related to fairness in model updates and improving efficiency better than state-of-the-art alternatives.…”
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