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. …”
Get full text

Optimization of distribution networks using quantum annealing for loss reduction and voltage improvement in electrical vehicle parking management by Naser Rashnu, Babak Mozafari, Reza Sharifi

“…Overall, this study presents a robust and scalable optimization strategy for building more efficient, resilient, and sustainable smart distribution systems.…”
Get full text

Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany by Loukas Kyriakidis, Rushit Kansara, Maria Isabel Roldán Serrano

“…To solve the resulting nonlinear and constrained optimization problem at each RHA iteration, we propose a novel hybrid algorithm that combines Bayesian optimization (BO) with the Interior Point OPTimizer (IPOPT). While global deterministic and stochastic optimization methods are frequently used in practice, they often suffer from high computational costs and slow convergence, particularly when applied to large-scale, nonlinear problems with complex constraints. …”
Get full text

Two-stage multi-timescale optimal scheduling for electricity-hydrogen coupling systems based on scenario approach and deep reinforcement learning by CHEN Zhe, WEI Meijia, LIN Da, LI Zhihao, CHEN Jian

“…The short-term model focuses on minimizing the systems’ operational costs and is solved using the deep deterministic policy gradient （DDPG） algorithm. Finally， case study simulations demonstrate that the proposed method effectively facilitates hydrogen energy shifting， smooths fluctuations in wind and solar output， verifying the method’s effectiveness.…”
Get full text

Enhancing Security With Hybrid Active- Passive RIS: A DRL Approach Against Eavesdropping and Jamming by Abdul Wahid, Syed Zain Ul Abideen, Nouman Imtiaz, Mian Muhammad Kamal, Abdullah Alharbi, Amr Tolba, M. A. Al-Khasawneh, Inam Ullah

“…To tackle this, we employ a Deep Reinforcement Learning (DRL) approach using the Deep Deterministic Policy Gradient (DDPG) algorithm, enabling efficient and dynamic optimization. …”
Get full text

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. …”
Get full text

Advances in Hosting Capacity Assessment and Enhancement Techniques for Distributed Energy Resources: A Review of Dynamic Operating Envelopes in the Australian Grid by Naveed Ali Brohi, Gokul Thirunavukkarasu, Mehdi Seyedmahmoudian, Kafeel Ahmed, Alex Stojcevski, Saad Mekhilef

“…This paper reviews state-of-the-art HC assessment methods, including deterministic, stochastic, time-series, and AI-based approaches. …”
Get full text

On the Synergy of IoMT Devices and Ceiling-Mounted Systems for Advanced Medical Data Analytics by Andreas Andreou, Constandinos X. Mavromoustakis, Evangelos K. Markakis, Athina Bourdena, George Mastorakis

“…Deep Reinforcement Learning (DRL) methods solve the resource allocation challenge under realistic constraints. …”
Get full text

Uncertainty CNNs: A path to enhanced medical image classification performance by Vasileios E. Papageorgiou, Georgios Petmezas, Pantelis Dogoulis, Maxime Cordy, Nicos Maglaveras

“…Uncertainty quantification (UQ) is important as it helps decision-makers gauge their confidence in predictions and consider variability in the model inputs. Numerous deterministic deep learning (DL) methods have been developed to serve as reliable medical imaging tools, with convolutional neural networks (CNNs) being the most widely used approach. …”
Get full text

LIGHTWEIGHT DESIGN FOR OVERHAUL TOOLING SUPPORT SEAT BASED ON TOPOLOGY OPTIMIZATION AND SIX SIGMA ROBUSTNESS by WANG ZiNing, WU JianJun, XIANG JianMing, WANG BaiSong, JIN YingQi

“…The results show that reliability of the design variables,strength and stiffness are all 1,reaching eight sigma level,the support seat’s weight is reduced by 67. 0% and the lightweight effect is remarkable; compared with the support seat’s traditional deterministic optimization design after topology optimization,this method enhances the strength and stiffness of the support seat,meanwhile,improves the reliability of the optimization design,the robustness of the strength,the robustness of the stiffness and the consistency of the weight. …”
Get full text

On the accurate computation of expected modularity in probabilistic networks by Xin Shen, Matteo Magnani, Christian Rohner, Fiona Skerman

“…In this paper, we implement and compare our method and various general approaches for expected modularity computation in probabilistic networks. …”
Get full text

Solving the Traveling Salesman Problem Based on The Genetic Reactive Bone Route Algorithm whit Ant Colony System by Majid Yousefikhoshbakht, Nasrin Malekzadeh, Mohammad Sedighpour

“…Because this problem is a non-deterministic polynomial (NP-hard) problem in nature, a hybrid meta-heuristic algorithm called REACSGA is used for solving the TSP. …”
Get full text

Microbial composition, assembly, and functional characteristics of generalized and specialized subcommunities under flooded paddy fields: long-term pesticide versus non-pesticide m... by Jing-Wen Wang, Jing-Wen Wang, Cai-Ting Han, Cai-Ting Han, Cai-Ting Han, Dong-Ming Wu, Dong-Ming Wu, Dong-Ming Wu, Wei Zhou, Wei Zhou, Miao Gao, Miao Gao, Yu-Shuang Li

Get full text

Joint Resource Allocation for V2X Sensing and Communication Based on MADDPG by Zhiyong Zhong, Zhangyou Peng

“…Integrated Sensing and Communication (ISAC) technology is essential for enhancing spectrum efficiency and reducing resource overhead. However, this also demands a more intelligent and efficient resource allocation framework for next-generation vehicular networks. …”
Get full text

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. …”
Get full text

Geometric thermodynamics of reaction-diffusion systems: Thermodynamic trade-off relations and optimal transport for pattern formation by Ryuna Nagayama, Kohei Yoshimura, Artemy Kolchinsky, Sosuke Ito

“…We also show that a similar geometric method further decomposes the entropy production rate into detailed contributions, e.g., the dissipation from each point in real or wavenumber space. …”
Get full text

A robust optimization model for allocation-routing problems under uncertain conditions. by Tingting Zhang, Yanqiu Liu

“…Developing a scientific and efficient rescue plan is crucial. One of the key issues is integrating facility location and casualty allocation in emergency medical services, an area rarely explored in existing research. …”
Get full text

Probabilistic Forecasting of Provincial Regional Wind Power Considering Spatio-Temporal Features by Gang Li, Chen Lin, Yupeng Li

“…The case study shows that the model proposed in this paper improves the interval prediction performance by at least 12.3% and reduces the deterministic prediction root mean square error (RMSE) by at least 19.4% relative to the benchmark model.…”
Get full text

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. …”
Get full text

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. …”
Get full text