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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Rhizosphere-associated bacterial and fungal communities of two maize hybrids under increased nitrogen fertilization by Qing Liu, HongCui Dai, Hao Cheng, Guodong Shao, Liang Wang, Hui Zhang, Yingbo Gao, Kaichang Liu, Xiaomei Xie, Junhua Gong, Xin Qian, Zongxin Li

“…Nevertheless, the effects of heightened nitrogen fertilizer demand of these crops on the composition and assembly of soil microbial communities in agricultural production require further elucidation.MethodsIn this study, the effects of four nitrogen fertilizer managements on rhizosphere bacterial and fungal community assembly, co-occurrence network and function of two maize hybrids (LD981 and DH605) were compared.Results and discussionFindings revealed that the bacterial community was primarily shaped by deterministic processes, while stochastic processes played a pivotal role in fungal community assembly. …”
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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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A Robust Longitudinal Control Strategy of Platoons under Model Uncertainties and Time Delays by Na Chen, Meng Wang, Tom Alkim, Bart van Arem

“…Automated vehicles are designed to free drivers from driving tasks and are expected to improve traffic safety and efficiency when connected via vehicle-to-vehicle communication, that is, connected automated vehicles (CAVs). …”
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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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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 Hybrid Path Planning Framework Integrating Deep Reinforcement Learning and Variable-Direction Potential Fields by Yunfei Bi, Xi Fang

“…Experimental results show that the improved algorithm effectively mitigates the trajectory oscillation of the robot and can efficiently solve the problems of local optimum and trap obstacles in the APF method. …”
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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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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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Leading Degree: A Metric for Model Performance Evaluation and Hyperparameter Tuning in Deep Learning-Based Side-Channel Analysis by Junfan Zhu, Jiqiang Lu

“…To attain an effective generic side-channel evaluation metric, we investigate the deterministic component of power consumption, find that the elements of score vector under a key follow a linearly transformed chi-square distribution approximately, and some wrong key hypotheses usually with top scores provide great assistance in model performance evaluation, and finally we propose a new metric called Leading Degree (LD) as well as its simplified version LD-simplified for measuring model performance, which offers similar accuracy but much better generality and efficiency compared with the classical side-channel benchmark metric TGE1, and offers similar generality and efficiency but significantly better accuracy compared with recently proposed sidechannel metrics like Label Correlation and Cross Entropy Ratio. …”
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Research on Long-Term Scheduling Optimization of Water–Wind–Solar Multi-Energy Complementary System Based on DDPG by Zixing Wan, Wenwu Li, Mu He, Taotao Zhang, Shengzhe Chen, Weiwei Guan, Xiaojun Hua, Shang Zheng

“…To address the challenges of high complexity in modeling the correlation of multi-dimensional stochastic variables and the difficulty of solving long-term scheduling models in continuous action spaces in multi-energy complementary systems, this paper proposes a long-term optimization scheduling method based on Deep Deterministic Policy Gradient (DDPG). …”
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A simple model considering spiking probability during extracellular axon stimulation. by Frank Rattay, Thomas Tanzer

“…However, most computer simulation studies for neuroprosthetic applications calculate thresholds for neural targets with a deterministic model and by reducing the sigmoid curve to a step function, they miss an important information about the control signal, namely how the spiking efficiency increases with stimulus intensity. …”
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Performance estimation of a steam-turbine driven multistage compressor system by Aleksa Miladinović, Jasna Stajić – Trošić, Mirjana Kijevčanin, Vladimir Stijepović, Sabla Y. Alnouri, Mirko Stijepović

“…As such, the method's effectiveness was demonstrated with model efficiencies closely matching design values within 2–10 % deviation for most stages, and highlighting areas for improvement where deviations reached up to 37 % in later stages.…”
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Improved Multiverse Optimization Algorithm for Fuzzy Flexible Job-Shop Scheduling Problem by Jin-Cheng Fang, A-Feng Zeng, Shao-Feng Zheng, Wen-Di Zhao, Xu He

“…An improved multiverse optimization (IMVO) algorithm is proposed herein for the fuzzy flexible job-shop scheduling problem pertaining to the non-deterministic polynomial-time hard (NP-hard) problem. …”
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A Comprehensive Review on the Integration of Renewable Energy Through Advanced Planning and Optimization Techniques by Carlos Barrera-Singaña, María Paz Comech, Hugo Arcos

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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

“…[Methods] To address this， this paper first constructs RE generation scenarios using Latin hypercube sampling （LHS） and modified k-means clustering， verifying their reserve feasibility， while transforming reserve-infeasible scenarios into extreme scenario sets. …”
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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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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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Multi-user joint task offloading and resource allocation based on mobile edge computing in mining scenarios by Siqi Li, Weidong Li, Wanbo Zheng, Yunni Xia, Kunyin Guo, Qinglan Peng, Xu Li, Jiaxin Ren

“…To address this issue, this paper proposes a method that combines partial offloading with collaborative mobile edge computing (MEC). …”
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