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    Prediction of rolling bearing performance degradation based on whale optimization algorithm and backpropagation model by Jingyue Wang, Yuntong Han, Haotian Wang, Jianming Ding, Cai Yi

    Published 2025-03-01
    “…The dissertation proposes a prediction model that enhances the BP (Backpropagation) neural network using the WOA (Whale Optimization Algorithm) to address the issue of local convergence during prediction. …”
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    Article
  5. 485

    Application of machine learning algorithm for prediction of abortion among reproductive age women in Ethiopia by Angwach Abrham Asnake, Alemayehu Kasu Gebrehana, Hiwot Altaye Asebe, Beminate Lemma Seifu, Bezawit Melak Fente, Meklit Melaku Bezie, Mamaru Melkam, Sintayehu Simie Tsega, Yohannes Mekuria Negussie, Zufan Alamrie Asmare

    Published 2025-05-01
    “…Therefore, this study employed machine learning algorithms to predict abortion in Ethiopia and identify its predictors using nationally representative data. …”
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    Article
  6. 486

    Constructing and Predicting Solutions for Different Families of Partial Differential Equations: A Reliable Algorithm by Mubashir Qayyum, Amna Khan

    Published 2022-01-01
    “…This algorithm estimates convergent series with an easy-to-use way of finding solution components through symbolic computation. …”
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    Article
  7. 487

    Adaptive random early detection algorithm based on network traffic level grade prediction by Debin WEI, Chengsheng PAN, Li YANG, Zuoren YAN

    Published 2023-06-01
    “…In view of the problem that the calculation of average queue length and maximum packet drop probability in random early detection algorithm and its variants reflect the changes of network traffic slowly, an adaptive random early detection algorithm based on network traffic level grade prediction was proposed.Based on the statistical characteristics of self-similar network traffic, the transition probability table of network traffic level grade was established, and a grade prediction method of self-similar network traffic level with low complexity and high accuracy was proposed.Furthermore, the prediction results were applied to calculate the average queue length in equal interval and adjust the maximum packet drop probability.Under the condition of fixed and variable bottleneck link capacity, it is found that regardless of the degree of self-similarity of network traffic, the proposed algorithm can improve the throughput and packet loss rate, especially when the Hurst parameter is large and the traffic is light.…”
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  8. 488

    Green Ground: Construction and Demolition Waste Prediction Using a Deep Learning Algorithm by Wadha N. Alsheddi, Shahad E. Aljayan, Asma Z. Alshehri, Manar F. Alenzi, Norah M. Alnaim, Maryam M. Alshammari, Nouf K. AL-Saleem, Abdulaziz I. Almulhim

    Published 2025-06-01
    “…Different types of waste lack an efficient and accurate method for classification, especially in cases that require the rapid processing of materials. A deep learning prediction model based on a convolutional neural network algorithm was developed to classify and predict the types of construction and demolition waste (CDW). …”
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    Article
  9. 489

    Traffic Prediction of Space-Integrated-Ground Information Network Based on Improved LSTM Algorithm by Chengsheng PAN, Yufu WANG, Li YANG

    Published 2020-12-01
    “…The space-integrated-ground information network is easy to interrupt and the traffi c fl uctuation is not stable due to the problems of high traffi c burst and topological time-varying, which makes the traffi c prediction diffi cult much higher than the ground.In order to solve this problem, an improved LSTM algorithm was put forward.Firstly, the traffi c autocorrelation was judged by analyzd the infl uence of the lag variable of traffi c sequence on the predicted value; Secondly, the noise and breakpoint of the training set were eliminated by replacing the interruption with the predicted value; Finally, Dropout algorithm was used to reduce the impact of noise and neural network over fi tting, and accurately predict the traffi c data of the integrated intelligent network.The simulation results showed that in OPNET simulation environment, compared with other algorithms, the accuracy of this algorithm was improved by 59.21%, and the training speed of the algorithm was improved by 11.11%, which could provide eff ective data support for the overall scheduling of the integrated intelligent network.…”
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  10. 490

    Predictive PID Control for Automated Guided Vehicles Using Genetic Algorithm and Machine Learning by Kinza Nazir, Yong-Woon Kim, Yung-Cheol Byun

    Published 2025-01-01
    “…Specifically, the GA-optimized true PID values achieved a mean error of 11.8402, while the SVR-predicted PID values had a mean error of 15.4438, with SVR attaining a recall of 86.55%. …”
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    An Intelligent Trajectory Prediction Algorithm for Hypersonic Glide Targets Based on Maneuver Mode Identification by Mingjie Li, Chijun Zhou, Lei Shao, Humin Lei

    Published 2022-01-01
    “…To improve the prediction precision for hypersonic glide targets, based on the analysis of the target’s maneuver characteristic, an intelligent trajectory prediction algorithm based on the maneuver mode identification is proposed in this paper. …”
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  13. 493

    Algorithm of calculation of predicted concentration (PEC) for evaluation of the environmental risk of veterinary medicinal products by Viviana Ciuca, V. V. Safta, Romeo Teodor CRISTINA

    Published 2018-12-01
    “…The paper presents an algorithm for calculating predictable concentrations for environmental factors: soil, water, sediment required for environmental risk assessment of veterinary medicinal products. …”
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    Prediction of Urban Scale Expansion Based on Genetic Algorithm Optimized Neural Network Model by Hewu Kuang

    Published 2022-01-01
    “…A genetic algorithm BP neural network (GA-BP) optimized by the genetic algorithm is used to shorten the running time of the algorithm and improve the prediction accuracy, but it is easy to fall into local solution. …”
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  17. 497

    An improved algorithm for prediction of vehicle trajectories using short-term goal-driven network by Abdalla Tawfik, Zaki Nossair, Roaa Mubarak

    Published 2025-05-01
    “…Conclusion This article presents an improved algorithm for predicting vehicle trajectories using short-term goals. …”
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    A Research Approach to Port Information Security Link Prediction Based on HWA Algorithm by Zhixin Xia, Zhangqi Zheng, Lexin Bai, Xiaolei Yang, Yongshan Liu

    Published 2024-11-01
    “…Because of this, this paper proposes an algorithm called hypergraph-based link prediction with self-attention (HWA) to solve the above problems. …”
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