Research Article
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 |