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巴西大型物流公司的真实数据库,每日预测订单数据集

巴西大型物流公司的真实数据库,每日预测订单数据集

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Business Regression

Data Set Information:The database was collected during 60 days, this is a real database of a Brazilian company of large......

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    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Data Set Information:

    The database was collected during 60 days, this is a real database of a Brazilian company of large logistics. Twelve predictive attributes and a target that is the total of orders for daily. treatment


    Attribute Information:

    The dataset was collected during 60 days, this is a real database of a brazilian logistics company. The dataset has twelve predictive attributes and a target that is the total of orders for daily treatment. The database was used in academic research at the Universidade Nove de Julho.
    .arff header for Weka:
    @relation Daily_Demand_Forecasting_Orders
    @attribute Week_of_the_month {1.0, 2.0, 3.0, 4.0, 5.0}
    @attribute Day_of_the_week_(Monday_to_Friday) {2.0, 3.0, 4.0, 5.0, 6.0}
    @attribute Non_urgent_order integer
    @attribute Urgent_order integer
    @attribute Order_type_A integer
    @attribute Order_type_B integer
    @attribute Order_type_C integer
    @attribute Fiscal_sector_orders integer
    @attribute Orders_from_the_traffic_controller_sector integer
    @attribute Banking_orders_(1) integer
    @attribute Banking_orders_(2) integer
    @attribute Banking_orders_(3) integer
    @attribute Target_(Total_orders) integer

    Relevant Papers:

    Ferreira, R. P., Martiniano, A., Ferreira, A., Ferreira, A., & Sassi, R. J. (2016). Study on daily demand forecasting orders using artificial neural network. IEEE Latin America Transactions, 14(3), 1519-1525.


    Citation Request:

    Ferreira, R. P., Martiniano, A., Ferreira, A., Ferreira, A., & Sassi, R. J. (2016). Study on daily demand forecasting orders using artificial neural network. IEEE Latin America Transactions, 14(3), 1519-1525.


    Creators original owner and donors: Ricardo Pinto Ferreira (1), Andrea Martiniano (2), Arthur Ferreira (3), Aleister Ferreira (4) and Renato Jose Sassi (5). E-mail address: kasparov '@' uni9.pro.br (1), andrea.martiniano '@' gmail.com (2), arthur2.ferreira '@' usp.br (3), aleisterferreira '@' hotmail.com (4), sassi '@' uni9.pro.br (5) - PhD student (1, 2), Graduation student (3, 4), Prof. Doctor (5).

    Universidade Nove de Julho - Post-Graduation Program in Informatics and Knowledge Management.

    Address: Rua Vergueiro, 235/249 Liberdade, Sao Paulo – SP, Brazil. Zip code: 01504-001.

    Website: http://www.uninove.br

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