Demand Prediction of Emergency Supplies under Fuzzy and Missing Partial Data

Algorithm 1

Input: Disaster information data set containing missing values

Output: Complete disaster information data set

(1) Initialization

(2) Set test conditions

(3)  FOR each target sample in X

(4)     FOR each candidate sample

(5)    Calculate grey relation degree

(6)    For sorting, candidate samples are selected

(7)    Fill missing information for the candidate samples by combining weight values

(8)    IF the result conforms to the test conditions

(9)     THEN fill the next target sample

(10)      ELSE change value and re-fill.

(11)    END FOR

(12) END FOR