Sentiment Analysis Algorithm Based on Deep Transfer Learning for Multi-Source Data Fusion by Long Qin

“…The experiment outcomes indicate that the artificial bee colony-improved particle swarm optimization algorithm designed in the study has the minimum convergence value under single-peak and multi-peak test functions, with a standard deviation of less than 0.25 and a success rate of 100% in optimization. …”
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Design Parameter Optimization of Self-centering Pier Based on Deep Learning by Weike ZHANG, Zhengnan LIU, Xingchong CHEN, Jiawei TANG

“…A finite element structural agent model created through the deep learning method can incorporate random parameters related to geometric and material mechanical properties to improve the model’s robustness and the self-centering pier’s multi-objective optimization efficiency.…”
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Enhancing LoRaWAN Performance Using Boosting Machine Learning Algorithms Under Environmental Variations by Maram A. Alkhayyal, Almetwally M. Mostafa

“…Bayesian Optimization was applied to fine-tune hyperparameters to improve model accuracy. …”
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Resource scheduling algorithm of satellite communication system for future multi-beam dense networking by Yuanzhi HE, Cong PENG, Jihong YU, Yun LIU

“…The resource scheduling problem of satellite communication systems under the condition of high-dynamic and resource limitation was studied.A resource scheduling model for satellite communication systems was established based on time window, energy consumption, number of channels, user priority and task suddenness.Considering the disadvantages of slow initial search speed and weak local search ability, the improved ant colony algorithm based on construction of initial solution set and extra pheromone deposition was proposed to solve the resource scheduling problem.The optimization characteristics of the number of completed tasks, priority and scheduling completion time were simulated and analyzed.The results show that the algorithm has a fast convergence rate.Compared with the same type optimization algorithm, the algorithm has high scheduling efficiency, therefore, it is suitable for scheduling satellite communication system resources for multi-beam dense networking in the future.…”
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A Distribution Network Expansion Project Classification Model Based on Data Augmentation and Dimensionality Reduction Method by Xin ZHOU, Jingxing LIN, Zhiwei XIE, Zheng ZHANG, Ruduo LIANG, Zuhong OU

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Improving Random Forest Algorithm for University Academic Affairs Management System Platform Construction by Jinyang Dai

“…In view of the complexity, heterogeneity, and security of college educational administration data and the difficulty of predicting and analyzing college students’ achievements, this paper designs a college educational administration management system platform based on improved random forest algorithm. Combining the advantages of three data-driven prediction algorithms, namely, random forest, extreme gradient boosting (XGBoost), and gradient boosting decision tree (GBDT), a model based on improved random forest algorithm is proposed. …”
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Framework for truck–RPAS hybrid models in last-mile delivery by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte

“…To balance operating cost, service time, regulatory risk, and energy usage, a novel multi-objective mixed-integer linear programming model is developed. High-quality Pareto-optimal solutions are produced by the non-dominated sorting genetic algorithm II, which methodically manages trade-offs between the conflicting goals. …”
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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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Comparative analysis of machine learning models for the detection of fraudulent banking transactions by Pedro María Preciado Martínez, Ricardo Francisco Reier Forradellas, Luis Miguel Garay Gallastegui, Sergio Luis Náñez Alonso

“…Using data from 565,000 real-world transfers, models based on algorithms such as Random Forest, Neural Networks and Naive Bayes were built and tested. …”
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Deployment of On-Orbit Service Vehicles Using a Fuzzy Adaptive Particle Swarm Optimization Algorithm by Yaxiong Li, Xinglong Sun, Xinxue Liu, Jian Wu, Qingguo Liu

“…Second, an assignment optimization model of OSVs is established based on the discrete particle swarm optimization (DPSO) algorithm, laying the foundation of the next optimization model. …”
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Frequency minimum inertia calculation of complex power systems based on an improved simulated annealing algorithm by Qiang Zhang, Qi Jia, Tingqi Zhang, Hui Zeng, Chao Wang, Wansong Liu

“…Then, based on the whole process of frequency response, we construct a power system minimum inertia assessment model taking into account the virtual inertia of new energy sources, and introduce an improved simulated annealing algorithm to solve the problem; the results validate the accuracy of the method through the IEEE-14 node model; the discussion section points out that this method provides a feasible solution for the inertia situational awareness of power system, which is helpful for the optimization of the operation, and also proposes that in the future we can take into account more uncertainties to improve the model and algorithm and to enhance the practicability and adaptability of this method. …”
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Optimizing Bi-LSTM networks for improved lung cancer detection accuracy. by Su Diao, Yajie Wan, Danyi Huang, Shijia Huang, Touseef Sadiq, Mohammad Shahbaz Khan, Lal Hussain, Badr S Alkahtani, Tehseen Mazhar

“…We employed traditional hand-crafted features, such as Gray Level Co-occurrence Matrix (GLCM) features, in conjunction with traditional machine learning algorithms. To explore the potential of deep learning, we also optimized and implemented a Bidirectional Long Short-Term Memory (Bi-LSTM) network for lung cancer detection. …”
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Do Sharpness-Based Optimizers Improve Generalization in Medical Image Analysis? by Mohamed Hassan, Aleksandar Vakanski, Boyu Zhang, Min Xian

“…These sharpness-based optimizers have shown improvements in model generalization compared to conventional stochastic gradient descent optimizers and their variants on general domain image datasets, but they have not been thoroughly evaluated on medical images. …”
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Combining 3-Opt and Improved Discrete Cuckoo Search Algorithm for the Traveling Salesman Problem by A. Sarucan, M. F. Berkaya

“…For 500 iterations, the average best solution of the proposed method differed from the average optimal solution by 0.07%. In the results of the improved discrete cuckoo search algorithm (CSA), this rate was calculated to be 0.08%. …”
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GRL-ITransformer: An Intelligent Method for Multi-Wind-Turbine Wake Analysis Based on Graph Representation Learning With Improved Transformer by Kang Han, Li Xu

“…In our study, we propose a graph representation learning model with improved Transformer (GRL-ITransformer) to better integrate feature information, so that the model can capture the dynamic time relationship of different variables and establish its spatial relationship, striving to enhance the precision in predicting wind turbine wake field. …”
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An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem by Jianxia Zhang, Jianxin Zhang, Feng Zhang, Minglu Chi, Linbin Wan

“…At last, the economic load dispatch problem could be optimized by the proposed improved symbiosis particle swarm optimization algorithm. …”
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Improving Sleep Disorder Diagnosis Through Optimized Machine Learning Approaches by Md. Atiqur Rahman, Israt Jahan, Maheen Islam, Taskeed Jabid, Md Sawkat Ali, Mohammad Rifat Ahmmad Rashid, Mohammad Manzurul Islam, Md. Hasanul Ferdaus, Md Mostofa Kamal Rasel, Mahmuda Rawnak Jahan, Shayla Sharmin, Tanzina Afroz Rimi, Atia Sanjida Talukder, Md. Mafiul Hasan Matin, M. Ameer Ali

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Feasibility of U-Net model for cerebral arteries segmentation with low-dose computed tomography angiographic images with pre-processing methods by Seong-Hyeon Kang, Kyuseok Kim, Jina Shim, Youngjin Lee

“…For the dataset to which both the optimized NLM algorithm and semiautomatic thresholding technique were applied, the segmentation model showed the most improved performance. …”
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Health State Prediction of Lithium-Ion Battery Based on Improved Sparrow Search Algorithm and Support Vector Regression by Deyang Yin, Xiao Zhu, Wanjie Zhang, Jianfeng Zheng

“…To enhance prediction performance, this paper introduces an SOH prediction model based on an improved sparrow algorithm and support vector regression (ISSA-SVR). …”
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Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nong... by Yuxiang Wang, Zhangwei Chen, Hongfei Zu, Xiang Zhang, Chentao Mao, Zhirong Wang

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