[1] 赵小柠,马昌喜.基于范例推理的灾害性地震应急物资需求预测研究[J].中国安全科学学报,2012,22(8):3-9.DOI:10.16265/j.cnki.issn1003-3033.2012.08.001. ZHAO X N,MA C X.Research on predicting emergency material demand after disastrous earthquake based on case-based reasoning[J].China Safety Science Journal, 2012, 22(8):3-9.DOI:10.16265/j.cnki.issn1003-3033.2012.08.001. [2] 刘德元,朱昌锋.基于案例模糊推理的应急物资需求预测研究[J].兰州交通大学学报,2013,32(1):138-141.DOI:10.3969/j.issn.1001-4373.2013.01.031. LIU D Y, ZHU C F.Forecasting research of emergency supplies demand on the case of fuzzy reasoning[J].Journal of Lanzhou Jiaotong University, 2013, 32(1):138-141.DOI:10.3969/j.issn.1001-4373.2013.01.031. [3] 王兰英,郭子雪,张玉芬,等.基于直觉模糊案例推理的应急物资需求预测模型[J].中国矿业大学学报,2015,44(4):775-780.DOI:10.13247/j.cnki.jcumt.000375. WANG L Y,GUO Z X,ZHANG Y F,et al.An emergency supplies demand prediction model based on intuitionistic fuzzy Case-based reasoning[J].Journal of China University of Mining &Technology, 2015,44(4):775-780.DOI:10.13247/j.cnki.jcumt.000375. [4] 赵一兵,高虹霓,冯少博.基于支持向量机回归的应急物资需求预测[J].计算机仿真,2013,30(8):408-412.DOI:10.3969/j.issn.1006-9348.2013.08.095. ZHAO Y B, GAO H N, FENG S B.Emergency material demand prediction based on support vector machine regression[J].Computer Simulation, 2013, 30(8):408-412.DOI:10.3969/j.issn.1006-9348.2013.08.095. [5] 王正新, 刘思峰.基于Fourier-GM(1, 1)模型的灾害应急物资需求量预测[J].系统工程,2013,31(8):60-64. WANG Z X, LIU S F.Forecasting demand of the disaster emergency supplies based on Fourier-GM(1,1)model[J].Systems Engineering, 2013, 31(8):60-64. [6] 钱枫林,崔健.BP神经网络模型在应急需求预测中的应用——以地震伤亡人数预测为例[J].中国安全科学学报,2013,23(4):20-25.DOI:10.16265/j.cnki.issn1003-3033.2013.04.017. QIAN F L, CUI J.Application of BP neural network analysis in forecasting emergency demand:A case study on earthquake casualty forecasting[J].China Safety Science Journal, 2013, 23(4):20-25.DOI:10.16265/j.cnki.issn1003-3033.2013.04.017. [7] SUN B Z, MA W M, ZHAO H Y.A fuzzy rough set approach to emergency material demand prediction over two universes[J].Applied Mathematical Modelling, 2013,37: 7062-7070. [8] SHEU J B.Dynamic relief-demand management for emergency logistics operations under large-scale disasters[J].Transportation Research Part E,2010,46(1):1-17. [9] MOHAMMADI R, GHOMI S M T F, ZEINALI F.A new hybrid evolutionary based RBF networks method for forecasting time series: A case study of forecasting emergency supply demand time series[J].Engineering Applications of Artificial Intelligence, 2014(36): 204-214. [10] 韩立岩,汪培庄.应用模糊数学[M].首都经贸大学出版社,1998. HAN L Y, WANG P Z.Applied fuzzy mathematics[M].Capital University of Economics and Business press, 1998. |