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  1. 101
  2. 102

    Integration of Genetic Algorithm with Machine Learning for Properties Prediction by Rathachai Chawuthai, Siripan Murathathunyaluk, Nalin Amornratthamrong, Run Arunchaipong, Amata Anantpinijwatna

    Published 2025-07-01
    “…To address this, Genetic Algorithms (GA) are employed to design chemical compounds that meet industrial requirements. …”
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    Article
  3. 103

    Prediction Method of Lithology Log Based on XGBoost Algorithm by CHU Qingjun, GE Yunlong, TONG Maosong, WANG Yan, AN Lyuxing, YU Chuanwu, JIA Xin

    Published 2024-12-01
    “…To solve this problem, an XGBoost algorithm-based model for predicting the photoelectric absorption cross-section index is established, and its prediction effect is compared with that of a neural network algorithm model. …”
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  4. 104

    5G network slicing algorithm based on prediction by Jiageng ZHANG, Min ZHU, Feng DU, Qi WANG, Jun LIU, Zhihai SUO, Li WANG

    Published 2021-09-01
    “…5G on line scenario needs short build time of network slice, it can use prediction algorithm to isolate network resource in advance to reduce the construction time of network slice.A 5G network slicing algorithm based on prediction was proposed, which used fourth square as cost function to predict the network resource requests with accepted accurate and lower complexity of algorithm.And then based on the prediction result, virtual nodes and links resource were allocated, and container was pulled up when network slice request arrives to network, the dynamic creation of network slices was completed.The simulation results show that the proposed algorithm can get 90% accurate of prediction, and reduce 50% construction time of network slice, and improve the network utilization ration,when new network slice reusing the original network slice.…”
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    Article
  5. 105

    Terrain Simplification Algorithm in Radio Wave Propagation Prediction by Dan Shi, Zhen Zhang, Fengshuo Wei, Cheng Lian

    Published 2022-01-01
    “…In order to study the influence of terrain simplification on the prediction of complex electromagnetic environment, a visibility algorithm used in the regular model of terrain and a probability-based power propagation model are proposed. …”
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    Article
  6. 106

    An empirical study of the naïve REINFORCE algorithm for predictive maintenance by Rajesh Siraskar, Satish Kumar, Shruti Patil, Arunkumar Bongale, Ketan Kotecha, Ambarish Kulkarni

    Published 2025-03-01
    “…Abstract Reinforcement Learning (RL) is a biologically inspired, autonomous machine learning method. RL algorithms can help generate optimal predictive maintenance (PdM) policies for complex industrial systems. …”
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    Article
  7. 107

    Naïve Bayes is an interpretable and predictive machine learning algorithm in predicting osteoporotic hip fracture in-hospital mortality compared to other machine learning algorithms. by Jo-Wai Douglas Wang

    Published 2025-01-01
    “…Overall, NB has much potential as an algorithm, due to its simplicity and interpretability whilst maintaining competitive predictive performance.…”
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    Article
  8. 108

    Impact of dimensionality reduction techniques on student performance prediction using machine learning by Koushik Roy, Huu-Hoa Nguyen, Dewan Md. Farid

    Published 2023-10-01
    “… This study addresses the crucial issue of predicting student performance in educational data mining (EDM) by proposing an Adaptive Dimensionality Reduction Algorithm (ADRA). …”
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    Article
  9. 109

    Impact of dimensionality reduction techniques on student performance prediction using machine learning by Koushik Roy, Huu-Hoa Nguyen, Dewan Md. Farid

    Published 2023-10-01
    “… This study addresses the crucial issue of predicting student performance in educational data mining (EDM) by proposing an Adaptive Dimensionality Reduction Algorithm (ADRA). …”
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    Article
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  14. 114

    Methods and Algorithms for Predictive Analytics of Time Series in Energy Consumption by Aleksandr Karmanov

    Published 2024-03-01
    “…Most of them should be viewed as early exploratory work demonstrating the potential of using machine learning algorithms to solve applied problems in energy consumption.…”
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    Article
  15. 115

    Model Reduction and Chattering Mitigation in Multi-Model Predictive Control for Quadrotor UAVs by Ghulam E. Mustafa Abro, Sufyan Ali Memon, Saddaf Rubab, Kaznah Alshammari, Faheem Khan

    Published 2025-01-01
    “…In order to resolve this discrepancy, we propose a Multi-Model Predictive Control (MMPC) approach that integrates Principal Component Analysis (PCA) for model reduction and employs linear quadrotor attitude models. …”
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  16. 116

    Chaos Time Series Prediction Based on Membrane Optimization Algorithms by Meng Li, Liangzhong Yi, Zheng Pei, Zhisheng Gao, Hong Peng

    Published 2015-01-01
    “…This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ,m) and least squares support vector machine (LS-SVM) (γ,σ) by using membrane computing optimization algorithm. …”
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    Application of machine learning algorithms in predicting pyrolytic analysis result by Thi Nhut Suong Le, A. V. Bondarev, L. I. Bondareva, A. S. Monakova, A. V. Barshin

    Published 2022-06-01
    “…In this paper, machine learning regression algorithms are applied for predicting one of the pyrolysis parameters of extracted samples based on the pyrolytic analysis results of the extracted and non-extracted samples. …”
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  19. 119

    Chronic Kidney Disease Prediction Based On Machine Learning Algorithms by Kethineni Likitha., Nithinchandra, Kumar Narendra, Sk Sajida Sultana.

    Published 2025-01-01
    “…This paper analyses the suitability of several machine learning algorithms for CKD prediction in consideration of health-related parameters like age, blood pressure, and blood glucose levels. …”
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  20. 120

    A novel model for malaria prediction based on ensemble algorithms. by Mengyang Wang, Hui Wang, Jiao Wang, Hongwei Liu, Rui Lu, Tongqing Duan, Xiaowen Gong, Siyuan Feng, Yuanyuan Liu, Zhuang Cui, Changping Li, Jun Ma

    Published 2019-01-01
    “…However, a stacking architecture can solve this problem by combining distinct algorithms and models. This study compares the performance of traditional time series models and deep learning algorithms in malaria case prediction and explores the application value of stacking methods in the field of infectious disease prediction.…”
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    Article