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    Comparison Between SAW and TOPSIS Methods in Selection of Broiler Chicken Meat Quality by Pungky Tri Kisworo Adi, Endang Sugiharti, Alamsyah Alamsyah

    Published 2018-05-01
    “…Decision support system is a system that can assist semi-structured and unstructured decision making, in which no one knows exactly how decisions should be made. …”
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    A predictive healthcare model using machine learning and psychological factors for medication adherence by Junwu Dong, Minyi Chu, Yirou Xu

    Published 2025-06-01
    “…Five machine learning algorithms – multiple logistic regression, decision tree, adaptive boosting, random forest and support vector machine (SVM) – were utilized to identify MAB levels and assess feature importance. …”
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    GrapeSLAM: UAV-based monocular visual dataset for SLAM, SfM and 3D reconstruction with trajectories under challenging illumination conditionszenodo by Kaiwen Wang, Sergio Vélez, Lammert Kooistra, Wensheng Wang, João Valente

    Published 2025-06-01
    “…SLAM (Simultaneous Localization and Mapping) is an efficient method for robot to percept surrendings and make decisions, especially for robots in agricultural scenarios. …”
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    Aggregating Contextual Information for Multi-Criteria Online Music Recommendations by Jieqi Liu

    Published 2025-01-01
    “…On the CAL500 dataset, CAMCMusic outperforms the FM algorithm by 11.9% in precision, 16.4% in recall, and 20% in F1-Score. …”
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    Construction of enhanced MRI-based radiomics models using machine learning algorithms for non-invasive prediction of IL7R expression in high-grade gliomas and its prognostic value... by Jie Zhou

    Published 2025-03-01
    “…Radiomics features were extracted from specific regions of interest, which were outlined by two physicians using 3D Slicer software. For selecting the most relevant features, we utilized the Minimum Redundancy Maximum Relevance (mRMR) and Recursive Feature Elimination (RFE) algorithms. …”
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  20. 1840

    Multi-Objective Scheduling for Green Flexible Assembly Job-Shop System via Multi-Agent Deep Reinforcement Learning With Game Theory by Xiao Wang, Zhongyuan Liang, Peisi Zhong, Dongmin Li, Hongqi Li, Mei Liu

    Published 2025-01-01
    “…These datasets and a case of the plunger pump production workshop scheduling scenario are designed to analyze the basic performance of this algorithm. The results show that the proposed algorithm compares with other single-indicator optimal algorithms with 9.47 per cent, 12.66 per cent and 22.86 per cent respectively for the three-evaluation metrics (GD, and HV), which contributed to solving the practical production problem of the manufacturing industry.…”
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