Quantum-enabled topological optimization of distributed energy storage for resilient black-start operations by Yinchi Shao, Yu Gong, Xiaoyu Wan, Xianmiao Huang, Shanna Luo, Yuntao Cao, Tao Zhang

“…By integrating quantum annealing algorithms, the framework efficiently addresses the combinatorial complexity of large-scale ESS placement and dispatch, outperforming traditional heuristic and classical optimization techniques in both computational speed and solution quality. …”
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Research review on intelligent object detection technology for coal mines based on deep learning by Fan ZHANG, Jiarong ZHANG, Haixing CHENG

“…However, deep learning object detection has a strong dependence on annotated datasets, and there are problems such as poor model interpretability and computational complexity. How to improve the accuracy, model adaptability, and computational efficiency of mine object detection is an urgent research topic in the field of mining artificial intelligence. …”
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Distributed Compensation With Parallelizability for Polarization Mode Dispersion Based on Learned Digital Backpropagation by Daobin Wang, Guangfu Li, Hui Yang, Wei Li, Ruiyang Xia, Chengqi Duan, Jianming Shang, Zanshan Zhao, Guanjun Gao

“…Finally, the improvement of the computational efficiency caused by parallelization is investigated. …”
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A study of the application of wet steam modeling for thermocompressor simulation in TVC desalination by Saeed Akbarnejad, Masoud Ziabasharhagh

“…Recently, the wet steam model, grounded in classical nucleation theory, has been utilized for computational fluid dynamics (CFD) simulations of thermocompressors and steam ejectors. …”
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Hybrid metaheuristic optimization for detecting and diagnosing noncommunicable diseases by Saleem Malik, S. Gopal Krishna Patro, Chandrakanta Mahanty, Saravanapriya Kumar, Ayodele Lasisi, Quadri Noorulhasan Naveed, Anjanabhargavi Kulkarni, Abdulrajak Buradi, Addisu Frinjo Emma, Naoufel Kraiem

“…The proposed framework introduces novel hybrid algorithms, including the Hierarchical Genetic Multiple Reduct Selection Algorithm (H-GMRA) and the Customized Function-based Particle Swarm Optimization with Rough Set Theory for NCD Feature Selection (CPSO-RST-NFS). These algorithms aim to address the challenges of feature selection, computational complexity, and disease classification accuracy. …”
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Gaussian beam migration in exploration seismology: methods, advantages and implementation by Donglin Zhang, Tong Zhou, Jidong Yang, Jieyuan Ning

“…Generally, seismic migration imaging methods can be categorized in pre-stack and post-stack techniques that are based on either wave-equation or ray-theory principles. Key methods include Kirchhoff Migration, a ray-theory-based approach; wave-equation-based techniques such as Reverse Time Migration (RTM); and Gaussian Beam Migration (GBM), which combines the flexibility of ray theory with the accuracy of wave-equation methods and is getting more attention recently. …”
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Methods to Quantitatively Evaluate the Effect of Shale Gas Fracturing Stimulation Based on Least Squares by DENG Cai, SUN Kexin, WEN Huan, HU Chaolang

“…The proposed model demonstrated several advantages over conventional approaches: 1) Enhanced accuracy and relevance: The model ensured highly accurate and practically applicable results by carefully defining fitting parameters and incorporating engineering constraints. 2) Robust theoretical foundation: It was grounded in established mathematical theory and principles of fluid mechanics. 3) Practicality and efficiency: The model featured low implementation costs and high computational efficiency, presenting a viable and promising alternative for field evaluations. …”
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A Comparison Performance Analysis of QoS WLANs: Approaches with Enhanced Features by Ioannis Papapanagiotou, Georgios S. Paschos, Michael Devetsikiotis

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Group Stable Matching Problem in Freight Pooling Service of Vehicle–Cargo Matching Platform by Linlin Kong, Min Huang

“…Based on the characteristics of the problem, the algorithm is improved by removing ineffective constraints and only using key constraints, significantly reducing computational complexity, optimizing the solving process, and greatly improving the model’s solution efficiency. …”
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Wood Species Recognition Based on Visible and Near-Infrared Spectral Analysis Using Fuzzy Reasoning and Decision-Level Fusion by Peng Zhao, Zhen-Yu Li, Cheng-Kun Wang

“…This method can rapidly achieve good recognition results, especially using small datasets, owing to its low computational time and space complexity.…”
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Fault Isolation in Network of State Automates by I. V. Bystrova, B. P. Podkopaev

“…To develop functional diagnostics method based on theoretical analysis allowing to decide fault isolation problem in networks of state automation and to reduce computational complexity and hardware redundancy.Materials and methods. …”
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Energy Efficiency Maximization for Device-to-Device Communication Underlaying Cellular Networks on Multiple Bands by Yuan Zhang, Yang Yang, Linglong Dai

“…Our theoretical analysis shows that the computational complexity of the proposed algorithm is significantly lower than that of the conventional branch and bound algorithm. …”
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Adaptive neural control for marine autonomous surface ships in cross-water scenarios by Xiang YE, Chao CHEN, Jian Xiong JIA, Hang CHEN

“…A novel specified performance function is constructed and combined with the barrier Lyapunov function (BLF) to transform the cross-water design, while the dynamic surface control technique is employed to reduce the system's computational complexity. Stability analysis is then performed by means of Lyapunov theory to demonstrate that all signals within the control system are bounded.ResultsThe simulation results show that the designed control scheme is not only capable of solving the cross-water tracking control of MASS, but that the tracking error can satisfy the convergence to a given bounded range within a predefined time offline. …”
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Decomposing Imaginary-Time Feynman Diagrams Using Separable Basis Functions: Anderson Impurity Model Strong-Coupling Expansion by Jason Kaye, Zhen Huang, Hugo U. R. Strand, Denis Golež

“…Focusing on the strong-coupling bold-line expansion of generalized Anderson impurity models, we show that our strategy reduces the computational complexity of evaluating an Mth-order diagram at inverse temperature β and spectral width ω_{max} from O((βω_{max})^{2M-1}) for a direct quadrature to O(M(log(βω_{max}))^{M+1}), with controllable high-order accuracy. …”
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The Bregman Modified Second APG Method for DC Optimization Problems by Lumiao Wang, Ziye Liu, Chunguang Liu

“…The results confirm that BAPGs effectively balances computational efficiency with relaxed smoothness requirements.…”
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An Efficient DoA Estimation Approach for 2-D Planar Array Antennas via Axial Decomposition of Antenna Current Green’s Function by Jeong-Wan Lee, Sung-Jun Yang

“…Through directional decomposition, 2-D array problem is transformed into two separate 1-D array analyses, reducing computational complexity from <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(M_{B}^{2}(N_{x}^{3} N_{y}^{3}))$ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(M_{B}^{2}(N_{x}^{3} + N_{y}^{3}))$ </tex-math></inline-formula>. …”
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A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy by Hua Zhan, Changxu Jiang, Zhen Lin

“…Secondly, a loop-based encoding method is employed to reduce the action space and complexity of the ADNDR. Then, based on graph theory, the DN structure is transformed into a dynamic network graph model, and a GCNDDPG-based ADNDR approach is proposed for the solution. …”
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A Fuzzy Hypergraph-Based Framework for Secure Encryption and Decryption of Sensitive Messages by Annamalai Meenakshi, Obel Mythreyi, Leo Mrsic, Antonios Kalampakas, Sovan Samanta

“…Traditional cryptographic systems based on numerical algorithms or standard graph theory are still open to structural and computational attacks, particularly in light of advances in computation power. …”
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Rate distortion optimization for adaptive gradient quantization in federated learning by Guojun Chen, Kaixuan Xie, Wenqiang Luo, Yinfei Xu, Lun Xin, Tiecheng Song, Jing Hu

“…To further reduce the computational complexity, we introduce the Kalman filter into the proposed approach. …”
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Mechanism of magnetic phase transition in correlated magnetic metal: insight into itinerant ferromagnet Fe3−δ GeTe2 by Yuanji Xu, Yue-Chao Wang, Xintao Jin, Haifeng Liu, Yu Liu, Haifeng Song, Fuyang Tian

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