The invention discloses a marine main engine spare part inventory consumption prediction method, and belongs to the technical field of marine main engine spare part prediction, and the method comprises the following steps: firstly, obtaining the historical use data of marine main engine spare parts, carrying out the normalization processing of the historical use data, carrying out the optimization of support vector machine regression parameters through employing an improved red fox optimization algorithm, and carrying out the optimization of the support vector machine regression parameters; and constructing a prediction model of the marine main engine spare parts. And finally, taking the historical data of the use condition of the spare parts of the marine main engine in a certain time period as a training set, training a prediction model of the training set, and outputting a prediction result after carrying out reverse normalization on a test result. According to the method, the reflection learning and elite reverse learning strategies are adopted in the red fox optimization algorithm, so that the convergence speed and the accuracy of the improved algorithm are improved, the parameters are optimized by using the red fox optimization algorithm, the situation that the prediction result is not ideal due to the fact that the parameters are set due to personal subjective factors is reduced, and the prediction efficiency is improved. And an accurate prediction service is provided for ship main engine spare part prediction.

    本发明公开了一种船舶主机备件库存消耗预测方法,属于船舶主机备件预测技术领域,所述方法包括以下步骤:首先获取船舶主机备件的历史使用数据,对其进行归一化处理,其次利用改进红狐优化算法中对支持向量机回归参数进行寻优,构建船舶主机备件的预测模型。最后某一时间段内船舶主机备件使用情况的历史数据作为训练集,训练其预测模型,然后对测试的结果进行反归一化后,输出预测结果。本发明通过在红狐优化算法中采用反思学习和精英反向学习策略,使得改进的算法在收敛速度和精确度上有所提高,同时利用红狐优化算法对参数寻优,降低了因个人主观因素设置参数造成的预测结果不理想的情况,为船舶主机备件预测提供精准的预测服务。


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Marine main engine spare part inventory consumption prediction method


    Weitere Titelangaben:

    一种船舶主机备件库存消耗预测方法


    Beteiligte:
    MENG GUANJUN (Autor:in) / HUANG JIANGTAO (Autor:in) / WEI YABO (Autor:in)

    Erscheinungsdatum :

    2023-06-23


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES / B63B Schiffe oder sonstige Wasserfahrzeuge , SHIPS OR OTHER WATERBORNE VESSELS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



    Marine large spare part storing and fixing device

    LIU ZHUOYU / YE QIAOMING / TANG CHUANKAI | Europäisches Patentamt | 2021

    Freier Zugriff

    Marine engine room double travelling crane large-scale spare part hanging and transporting method

    LI XIANG / LUO YAPING | Europäisches Patentamt | 2015

    Freier Zugriff

    Multi-Objective Models and Algorithms for System Spare Part Inventory Optimization

    Li, Z. / Gan, M. / Zong, J. et al. | British Library Conference Proceedings | 2009


    Multi-Objective Models and Algorithms for System Spare Part Inventory Optimization

    Li, Zongping / Gan, Mi / Zong, Junya et al. | ASCE | 2009


    Cost allocation in spare parts inventory pooling

    Wong, Hartanto | Online Contents | 2007