Showing 181 - 200 results of 10,454 for search '"machines"', query time: 0.06s Refine Results
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    MIP Models and Hybrid Algorithms for Simultaneous Job Splitting and Scheduling on Unrelated Parallel Machines by Duygu Yilmaz Eroglu, H. Cenk Ozmutlu

    Published 2014-01-01
    “…We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. …”
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    A Machine Learning Approach to Optimize, Model, and Predict the Machining Factors in Dry Drilling of Nimonic C263 by S. Lakshmana Kumar, V. Jacintha, A. Mahendran, R. M. Bommi, M. Nagaraj, Umamahesawari Kandasamy

    Published 2022-01-01
    “…Nimonic C263 is tough to machine aero alloys, and it is required to find a predictive model and to optimize the factors in drilling this alloy before the actual machining process. …”
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    Thermal management and biocompatibility in dry machining: An experimental study of ZrO2-based cutting tool for bone machining by Phanindra Addepalli, Worapong Sawangsri, Saiful Anwar Che Ghani

    Published 2025-01-01
    “…The study compares wet and dry machining to analyze the effects of temperature and cell behaviour. …”
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    Detecting Invalid Associations between Fare Machines and Metro Stations Using Smart Card Data by Pengfei Zhang, Zhenliang Ma, Xiaoxiong Weng

    Published 2021-01-01
    “…This paper deals with an invalid data problem in the automated fare collection (AFC) database caused by the erroneous association between the fare machines and metro stations, e.g., a fare machine located at Station A is wrongly associated with Station B in the AFC database. …”
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    Feature Selection and Parameter Optimization of Support Vector Machines Based on Modified Cat Swarm Optimization by Kuan-Cheng Lin, Yi-Hung Huang, Jason C. Hung, Yung-Tso Lin

    Published 2015-07-01
    “…The basic CSO algorithm was integrated with a local search procedure as well as the feature selection and parameter optimization of support vector machines (SVMs). Experiment results demonstrate the superiority of MCSO in classification accuracy using subsets with fewer features for given UCI datasets, compared to the original CSO algorithm. …”
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