A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production by Hongtao Hu, Yiwei Wu, Tingsong Wang

“…An improved solution algorithm based on particle swam optimization is developed to efficiently solve the proposed model. …”
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Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction by Qian Zeng, Xiaobo Li, Yixuan Chen, Minghao Yang, Xingbang Liu, Yuetian Liu, Shiwei Xiu

“…By leveraging attention parameters, ELPM acquires spatio-temporal adaptive weights, enabling accurate location predictions. We also design an improved service allocation strategy, MESDA, based on the Gray Wolf Optimization (GWO) algorithm. …”
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Subspace-based local compilation of variational quantum circuits for large-scale quantum many-body simulation by Shota Kanasugi, Yuichiro Hidaka, Yuya O. Nakagawa, Shoichiro Tsutsui, Norifumi Matsumoto, Kazunori Maruyama, Hirotaka Oshima, Shintaro Sato

“…We demonstrate the validity of the LSVQC algorithm through numerical simulations of a simple spin-lattice model and an effective model of a parent compound of cuprate superconductors, Sr_{2}CuO_{3}, constructed by the ab initio downfolding method. …”
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A Semi-Supervised Abbreviation Disambiguation Method Based on ACNN and Bi-LSTM by ZHANG Chun-xiang, PANG Shu-yang, GAO Xue-yao

“…Training corpus is extended by using Xgboost algorithm and LightGBM algorithm， and then expanded training corpus is input into this model. …”
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Developing an Efficient Calibration System for Joint Offset of Industrial Robots by Bingtuan Gao, Yong Liu, Ning Xi, Yantao Shen

“…Therefore, there are several lines in space parameterized by robot joint offsets only and all these lines were constrained by the same point, that is, the center of the PSD surface. Consequently, an optimization model was formulated and the Levenberg-Marquardt (LM) algorithm was employed to identify the joint offsets. …”
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A Method Adjusting Consistency and Consensus for Group Decision-Making Problems with Hesitant Fuzzy Linguistic Preference Relations Based on Discrete Fuzzy Numbers by Meng Zhao, Ting Liu, Jia Su, Meng-Ying Liu

“…Besides, an illustrative example and comparative analysis are conducted through the proposed calculation process and the optimization algorithm. Finally, the analysis on the threshold values is made to help the decision-maker determine critical consensus level. …”
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A Generalized Shape Function for Vibration Suppression Analysis of Acoustic Black Hole Beams Based on Fractional Calculus Theory by Jun Xu, Ning Chen

“…To obtain the best parameters of the shape function under various parameters, the Particle Swarm Optimization (PSO) algorithm is employed. The results demonstrate that by selecting appropriate ML parameters and viscoelastic materials, the dissipation characteristics of the structure can be significantly improved. …”
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Neural Network-Based Imitation Learning for Approximating Stochastic Battery Management Systems by Andrea Pozzi, Alessandro Incremona, Daniele Toti

“…Lithium-ion batteries play a pivotal role in enabling eco-friendly mobility, particularly in electric vehicles, but optimizing their charging process to improve battery lifespan, safety, and overall efficiency remains a significant challenge. …”
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A Robust Enhanced Ensemble Learning Method for Breast Cancer Data Diagnosis on Imbalanced Data by Zhenzhen Wang, Junde Xie, Jia Zhang

“…In addition, a data-driven based particle swarm optimization algorithm automatically is used to select the value of parameters for base classifiers. …”
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Performance Analysis of CO2 Systems Integrated with Ejector and Dedicated Mechanical Subcooling by Dai Baomin, Zhao Ruirui, Liu Shengchun, Qian Jiabao, Xu Tianyahui, Liu Chen, Yang Peifang

“…A thermodynamic model of the system was devised. Then, the discharge pressure and subcooling degree were optimized using a genetic algorithm by considering the coefficient of performance (COP) as the objective function. …”
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Prediction of Drifter Trajectory Using Evolutionary Computation by Yong-Wook Nam, Yong-Hyuk Kim

“…In contrast to existing numerical models that use the Lagrangian method, we used an optimization algorithm to predict the trajectory. …”
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Posture Recognition and Behavior Tracking in Swimming Motion Images under Computer Machine Vision by Zheng Zhang, Cong Huang, Fei Zhong, Bote Qi, Binghong Gao

“…The objectives are realized by moving target detection and tracking, Gaussian mixture model, optimized correlation filtering algorithm, and Camshift tracking algorithm. …”
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Cloud edge end network resource allocation for thermostatically controlled load aggregation regulation by Yi LIU, Xin WU

“…Thermostatically controlled load is a flexible load that controls temperature regulation, such as air conditioning and electric water heaters.As a crucial demand side resource, flexible aggregation and regulation of load clusters can fully mobilize clean energy consumption capacity and ensure the balance between supply and demand of the power grid.Due to the common occurrence of thermostatically controlled loads in commercial office buildings and residential areas, a relatively stable control and transmission method can be adopted.Therefore, an efficient hierarchical transmission network is introduced to achieve data transmission and information interaction between loads and the power grid, and to flexibly, real-time, and accurately utilize the adjustable potential of load clusters.Firstly, an information interaction architecture of load IoT which structured “central cloud-edge cloud-regional load controller-thermostatically controlled load”was proposed.Then, for the “end edge”part, considering the requirements of different aggregation control tasks, an improved clustering algorithm was used to classify the tasks and reduce transmission overhead.For the “end-side” part, an improved clustering algorithm was used to optimize the transmission distance.For the edge-cloud collaboration part, a subchannel resource allocation algorithm was designed based on stable matching and water injection algorithms.The binary particle swarm optimization algorithm was used to solve the task upload decision problem.Finally, the effectiveness of the proposed model and algorithm is verified through simulation, and comparative experiments are also conducted.…”
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Research on data completion and generation of downhole drilling tool attitude based on Long Short-Term Memory neural networks by Qiwei Liu, Fanmin Kong, Xiaolong Chen, Kang Li

“…To overcome these limitations, a Long Short-Term Memory (LSTM) model, a type of deep learning algorithm known for capturing complex time-series dependencies, is proposed for data completion. …”
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Well logging super-resolution based on fractal interpolation enhanced by BiLSTM-AMPSO by Jian Han, Yu Deng, Bing Zheng, Zhimin Cao

“…Specifically, mutation factors are introduced into the particle swarm optimization (PSO) algorithm to enhance search accuracy. …”
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Entropy-driven multi agent deep reinforcement learning for resilient distribution networks: coordinating MESS and microgrids by Changchun Cai, Fenglu Gan, Yong Cui, Bo Li, Shixi Hou

“…First, with critical load restoration as the objective function, coordinated optimization model for MESS dispatch and network reconfiguration is constructed, which comprehensively considers security constraints of both distribution networks and microgrids. …”
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Influence of artificial intelligence on higher education reform and talent cultivation in the digital intelligence era by Limin Qian, Weiran Cao, Lifeng Chen

“…Abstract In order to solve the problems of inefficient allocation of teaching resources and inaccurate recommendation of learning paths in higher education, this paper proposes a smart education optimization model (SEOM) by combining the improved random forest algorithm (RFA) based on adaptive enhancement mechanism and the Graph Neural Network (GNN) algorithm. …”
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Multidepot Recycling Vehicle Routing Problem with Resource Sharing and Time Window Assignment by Yong Wang, Xiuwen Wang, Xiangyang Guan, Jinjun Tang

“…In comparison with NSGA algorithm, the NSGA-II algorithm incorporates an elitist strategy, which can improve the computational speed and robustness. …”
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METRICS FOR EVALUATING CONSISTENCY IN DISTRIBUTED DATASTORES by Galyna Zholtkevych

“…This decision-making algorithm should be suitable for any business model and its requirements. …”
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GRU-based multi-scenario gait authentication for smartphones by Qi JIANG, Ru FENG, Ruijie ZHANG, Jinhua WANG, Ting CHEN, Fushan WEI

“…At present, most of the gait-based smartphone authentication researches focus on a single controlled scenario without considering the impact of multi-scenario changes on the authentication accuracy.The movement direction of the smartphone and the user changes in different scenarios, and the user’s gait data collected by the orientation-sensitive sensor will be biased accordingly.Therefore, it has become an urgent problem to provide a multi-scenario high-accuracy gait authentication method for smartphones.In addition, the selection of the model training algorithm determines the accuracy and efficiency of gait authentication.The current popular authentication model based on long short-term memory (LSTM) network can achieve high authentication accuracy, but it has many training parameters, large memory footprint, and the training efficiency needs to be improved.In order to solve the above problems a multi-scenario gait authentication scheme for smartphones based on Gate Recurrent Unit (GRU) was proposed.The gait signals were preliminarily denoised by wavelet transform, and the looped gait signals were segmented by an adaptive gait cycle segmentation algorithm.In order to meet the authentication requirements of multi-scenario, the coordinate system transformation method was used to perform direction-independent processing on the gait signals, so as to eliminate the influence of the orientation of the smartphone and the movement of the user on the authentication result.Besides, in order to achieve high-accuracy authentication and efficient model training, GRUs with different architectures and various optimization methods were used to train the gait model.The proposed scheme was experimentally analyzed on publicly available datasets PSR and ZJU-GaitAcc.Compared with the related schemes, the proposed scheme improves the authentication accuracy.Compared with the LSTM-based gait authentication model, the training efficiency of the proposed model is improved by about 20%.…”
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