Multi-clustering algorithm based on improved tensor chain decomposition by ZHANG Hongjun, ZHANG Zeyu, ZHANG Yingjiao, YE Hao, PAN Gaojun

“…The tensor train (TT) method was studied and improved in depth, which had significantly improved its performance in multi-clustering tasks by introducing a new optimization strategy. The innovations were mainly reflected in two aspects: firstly, a new tensor decomposition framework was proposed, which effectively reduced the storage cost and improved the computational efficiency by optimizing the objective function; secondly, the improved tensor decomposition technique was applied to three main multi-clustering algorithms, including self-weighted multi-view clustering (SwMC), latent multi-view subspace clustering (LMSC), and multi-view subspace clustering with intactness-aware similarity (MSC IAS), which significantly improved the accuracy and efficiency of clustering. …”
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A Fast Map Merging Algorithm in the Field of Multirobot SLAM by Yanli Liu, Xiaoping Fan, Heng Zhang

“…The simulated data is used as information sources in the other map to do partial map Monte Carlo localization; if localization succeeds, the relative pose hypotheses between the two maps can be computed easily. We verify these hypotheses using the rendezvous technique and use them as initial values to optimize the estimation by a heuristic random search algorithm.…”
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Variational autoencoder-based multipath clustering algorithm for terahertz channels by HAO Xinyu, LIAO Xi, ZHENG Xiangquan, WANG Yang, LIN Feng, CHEN Qianbin, ZHANG Jie

“…To address the shortcomings of multipath clustering algorithms in terahertz channel modeling, particularly in terms of multidimensional parameter adaptability and unsupervised feature separation, a variational autoencoder-based latent space multipath clustering (VAE-LMC) model was proposed. …”
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Design and implementation of codec based on BCH error correction algorithm by Wang Guan, Wei Jinghe, Yu Zongguang

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Trajectory Similarity Algorithm Based on DTW and Trajectory Point Compression by GAO Wei, QIAN Chengyang, ZHANG Qi, XIE Hongquan

“…Understanding the behavior characteristics of these holders through processing massive trajectory data has become an important issue to be addressed using trajectory similarity algorithms. To optimize the computational efficiency of the algorithm while maintaining its accuracy, this paper presents an algorithm based on an improved dynamic time warping (DTW) algorithm, i.e. the compression DTW (CN-DTW) algorithm to overcome the deficiencies of long running time and ill-conditioned alignment in the DTW algorithm. …”
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YOLO-Dynamic: A Detection Algorithm for Spaceborne Dynamic Objects by Haiying Zhang, Zhengyang Li, Chunyan Wang

“…Meanwhile, LASF_Neck employs a lightweight multi-scale architecture for optimized feature fusion and faster detection. The YOLO-Dynamic algorithm’s performance was validated on real-world images captured at Antarctic observatory sites. …”
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Lightweight insulator target detection algorithm based on improved YOLOX by Bing Zeng, Wei Hua, Dezhi Li, Zhihao Zhou, Hao Wan, Yunmin Xie, Tangbing Li, Yucong Chen, Jianglei Li, Shenli Wang, Shixun Fu, Zihan Jin, Wenhua Zhang

“…Finally, the σWIoU loss function replaces the traditional IoU to accelerate convergence and optimize overall performance. Experiments show that compared to the original YOLOX, the proposed algorithm reduces parameters by 53.41% to 4.164 M and computational load to 12.975G, with mAP increased by 1.3%, detection accuracy reaching 98.81%, and recall achieving 100%. …”
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Speech emotion recognition based on a stacked autoencoders optimized by PSO based grass fibrous root optimization by Chi Zeng, Jialing Li, Abbas Habibi

“…Specifically, a stacked autoencoder (SAE) serves as the primary model, and its performance is fine-tuned using a nature-inspired hybrid algorithm that combines particle swarm optimization (PSO) with Grass Fibrous Root Optimization (GFRO). …”
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Rehabilitation Technologies by Integrating Exoskeletons, Aquatic Therapy, and Quantum Computing for Enhanced Patient Outcomes by Fabio Salgado-Gomes-Sagaz, Vanessa Zorrilla-Muñoz, Nicolas Garcia-Aracil

“…This study also explored quantum computing techniques, such as the quantum approximate optimization algorithm (QAOA) and the quantum Fourier transform (QFT), to optimize controller tuning and improve real-time control, highlighting the potential of these advanced tools in refining rehabilitation devices.…”
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Biomimetic model for computing missing data imputation and inconsistency reduction in pairwise comparisons matrices. by Waldemar W Koczkodaj, Witold Pedrycz, Alexander Pigazzini, Laura P Pigazzini

“…The proposed regeneration method emulates three primary phases of a biological process: identifying the most damaged areas (by identifying inconsistencies in the pairwise comparison matrix), cell proliferation (filling in missing data), and stabilization (optimization of global consistency). An iterative algorithm is employed to correct inconsistencies and compute missing data imputations within the pairwise comparison matrix. …”
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Enhancing remote patient monitoring with AI-driven IoMT and cloud computing technologies by Vijay Kumar Damera, Ramesh Cheripelli, Narsaiah Putta, G. Sirisha, Deepthi Kalavala

“…The proposed TL-SAM framework effectively extracts spatial and spectral features from patient health data, optimizing classification accuracy. Furthermore, the model employs an Improved Wild Horse Optimization with Levy Flight Algorithm (IWHOLFA) for hyperparameter tuning, enhancing its predictive performance. …”
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Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

“…However, the MPC’s performance depends on the optimal tuning of its key parameters, a challenge addressed using the Multivariate Gaussian Mixture Model Continuous Ant Colony Optimization (MGMM-<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>ACO</mi><mi>R</mi></msub></semantics></math></inline-formula>) algorithm. …”
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From molecules to data: the emerging impact of chemoinformatics in chemistry by Anup Basnet Chetry, Keisuke Ohto

“…Emerging technologies, including quantum computing, hold promise for further revolutionizing the field by offering new capabilities for simulating and optimizing chemical processes. …”
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Hybrid Filter-Wrapper Feature Selection using Modified Flower Pollination Algorithm by Mohammad Ansari Shiri, Najme Mansouri

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An approach based on genetic algorithms and neural networks for QoS-aware IoT services composition by Rabah Boucetti, Ouassila Hioual, Sofiane Mounine Hemam

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Heterogeneous Differential Evolution for Numerical Optimization by Hui Wang, Wenjun Wang, Zhihua Cui, Hui Sun, Shahryar Rahnamayan

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Analysis of software methods for metal computed tomography artifact reduction: experimental research by A. V. Petraikin, Yu. A. Vasilev, Z. R. Artyukova, A. K. Smorchkova, D. S. Semenov, А. А. Baulin, A. A. Alikhanov, R. A. Erizhokov, O. V. Omelyanskaya

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Efficient Pathfinding on Grid Maps: Comparative Analysis of Classical Algorithms and Incremental Line Search by Amr Elshahed, Majid Khan Bin Majahar Ali, Ahmad Sufril Azlan Mohamed, Farah Aini Binti Abdullah, Ts. Lee Jian Aun

“…By restricting the search to this focused region and expanding only when necessary, ILS significantly reduces computational overhead while preserving optimality in cases where the underlying algorithm guarantees it, and delivering near-optimal paths in others. …”
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A Golden Jackal based optimal operation and optimization of a virtual power plant involving renewable resources by Anubhav Kumar Pandey, Chaima Mansour, Nandini K. K., Vinay Kumar Jadoun, Jayalakshmi N. S.

“…Furthermore, the scheduling of the VPP system is carried out on a day-ahead basis and the outcome in terms of cost and emission is compared with the available work in the literature and the result reveals the effectiveness of the system in terms of quality solutions sets for the objectives, minimum computational time and better convergence behavior. In particular, there is a reduction in cost by 2.1% and 0.62% when compared with the salp swarm algorithm and beluga whale algorithm followed by 2.12% and 1.18% in emission. …”
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Development and investigation of parallel model of bee colony algorithms for cryptanalysis problem solving by Yury O Chernyshev, Alexander S Sergeev, Alexander N Ryazanov, Evgeny O. Dubrov

“…Theoretical estimates of time complexity of the bee colony algorithm are given as the key data. Besides, the problem solution is provided: to find the required smallest number of processors of the homogeneous parallel computing systems with distributed memory, and a uniform plan for the implementation of operators for them, for the cryptanalysis algorithm based on the constructed information-logical graph data-logical graph, and for the preset time. …”
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