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Daily Demand Forecasting Orders Data Set
Download: Data Folder, Data Set Description

Abstract: The dataset was collected during 60 days, this is a real database of a brazilian logistics company.

Data Set Characteristics:  

Time-Series

Number of Instances:

60

Area:

Business

Attribute Characteristics:

Integer

Number of Attributes:

13

Date Donated

2017-11-21

Associated Tasks:

Regression

Missing Values?

N/A

Number of Web Hits:

98049


Source:

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


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
@data


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.


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