基于灰色预测模型的广州市城镇生活垃圾清运量预测

基于灰色预测理论,分别用GM(1,1)模型、分数阶GM(1,1)模型和新陈代谢GM (1,1)模型对广州市2015-2019年城镇生活垃圾清运量数据进行建模、检验和比较,结果表明新陈代谢GM(1,1)模型预测精度最高.预测2020-2024年广州市城镇生活垃圾清运量仍呈现长的趋势,在2024年将会突破1000万吨.     

基于动态无偏灰色马尔科夫模型的煤炭需求量预测

煤炭消费系统是一个复杂的非线性系统,具有随机性、非线性、动态性等特点,科学地预测煤炭消费量及其结构对于优化配置能源有重要意义.传统的单一预测方法预测精度较低.在对陕西省煤炭消费历史数据分析的基础上,构建了煤炭消费总量的GM(1,1)模型、灰色GM(1,1)预测模型和动态无偏的马尔科夫结构预测模型.拟合结果表明,动态无偏灰色马尔科夫模型既能消除传统灰色GM(1,1)模型的固有偏差,又能提高预测精度,其平均相对误差为2.10%,分别低于传统灰色GM(1,1)模型和一般灰色马尔科夫模型的17.37%和6.37%,可用于煤炭需求的预测,在此基础上对陕西省2017-2025年煤炭消费进行了预测,为未来能源消费发展规划提供依据.     

基于分数阶GM(1,1)与BP神经网络的电力负荷预测

传统的灰色GM(1,1)和BP神经网络模型存在对原始序列依赖高,收敛速度慢等缺点.将分数阶累加的思想引入GM(1,1)模型,再用逐层训练算法改进传统的BP神经网络.基于我国2010-2014年的电力数据,构建分数阶GM(1,1)与BP神经网络组合模型,预测2015年和2016年的总发电量.实证结果表明,该组合模型比GM(1,1)模型,分数阶GM(1,1)模型以及GM(1,1)与BP神经网络组合模型具有更好的数据拟合效果,更高的预测精度.     

动态的最佳维数GM(1,1)幂模型在基尼系数预测中的应用

针对传统灰色GM(1,1)预测模型维数确定困难、适用范围小和预测精度不高等局限性,提出了一种能处理复杂序列的动态的最佳维数GM(1,1)幂模型.最后以2003-2013年居民收入基尼系数为研究样本做预测分析,同时建立了传统GM(1,1)模型、经典GM(1,1)幂模型作为对比,结果表明:动态的最佳维数GM(1,1)幂模型的平均相对误差为0.08%,显著低于传统GM(1,1)模型的1.04%和经典GM(1,1)幂模型的0.85%.     

基于改进GM(1,1)模型的新疆煤炭消费预测

科学地预测煤炭消费量可为煤炭生产、进口、消费提供可靠的理论依据,建立了1998-2015年新疆煤炭消费的非线性回归的GM(1,1)模型,并预测了2016-2030年的值.研究表明:改进GM(1,1)模型的预测效果良好,新疆煤炭消费量在2016-2030年将持续出现增长趋势,但增速有所下降.     

基于改进灰色马尔科夫模型成品油消费预测

近年来中国经济放缓,成品油的消费一定程度上受到了抑制,2016年,我国汽柴油表观消费量首次较前年下降.成品油消费税率提高,导致部分成品油生产资本向新能源项目转移.根据GM(1,1)模型和马尔科夫模型时间序列预测的长短期互补,首先用GM(1,1)模型对成品油消费量进行预测,随后利用马尔科夫模型对GM(1,1)预测误差项的状态及状态概率进行预估,采用预测状态与其概率的乘积对GM(1,1)预测值进行修正.结果表明,改进后的灰色马尔科夫模型误差小,精度高,适于中长期预测.除此之外,组合模型还可以通过增加误差状态划分的个数,以提高模型预测的精度.     

组合GM(1,1)幂模型及其应用

GM(1,1)幂模型是灰色Verhulst模型的推广.由于初始条件选取影响GM(1,1)幂模型的精度,将平均相对误差函数分别看成是幂指数、发展系数、灰作用量的函数,利用蚁群算法进行参数辨识,从而建立多个单项GM(1,1)幂模型.利用这些单项模型建立了线性组合GM(1,1)幂模型,组合权系数利用最大相对误差最小化原则采用粒子群算法确定.实例表明,组合GM(1,1)幂模型的建模精度高于传统GM(1,1)幂模型,同时也说明方法是有效的和可行的,具有重要的理论意义.     

基于新陈代谢GM(1,1)模型的中国煤炭消费量预测分析

运用灰色系统理论,以中国2002-2012年的中国煤炭消费量建立了GM(1,1)和新陈代谢GM(1,1)预测模型.使用相对误差和残差平方和对两个模型的精度进行检验,对比表明,新陈代谢模型精度高于常规的GM(1,1)模型.使用平均弱化缓冲算子来表示能源政策对煤炭消费量的冲击,应用处理后的新陈代谢GM(1,1)模型对2015-2017年的煤炭消费量进行了预测.     

灰色预测GM(1,1)模型的改进及应用

应用自动寻优定权的方法和最小二乘法,研究了灰色系统理论中灰色预测GM(1,1)模型的预测公式的形成过程,发现灰色预测GM(1,1)模型在形成预测公式时对背景值和初始值的规定是不尽合理的,且现有的改进方法对灰色预测GM(1,1)模型的改进还不尽完善.为了提高灰色预测GM(1,1)模型的预测精度,提出并使用自动寻优定权对背景值进行选择,基于最小二乘法原理对灰色预测GM(1,1)模型的初始值进行改进.实例结果表明,提出的改进方法是有效和完善的,对灰色预测GM(1,1)模型的预测精度也有较大的提高.     

灰色GM(1,1)模型研究综述

GM(1,1)是灰色预测理论的核心模型和基础模型.从累加生成方法、初值优化、背景值优化、参数估计方法、模型性质和模型拓展的视角,梳理了GM(1,1)模型的研究进展.明确了有待进一步研究的问题,对GM(1,1)模型的未来研究方向提出了建议.     

基于灰色系统建模的上海城市居民可支配收入与消费支出关系的实证研究

按不同收入层次可支配收入水平与相应的消费支出关系分别建立GM(0,2)模型,分析不同层次收入群体的灰边际消费倾向变化规律;通过GM(1,2)建模,进一步分析了可支配收入对消费支出的驱动作用,研究了可支配收入与消费支出关系系统的协调性;通过对不同时段收入与支出关系的建模比较,进一步分析了不同层次收入群体灰边际消费倾向的动态变化,有效地改善了模型研究的局限性。     

中国农村居民消费结构的Panel Data模型分析

基于持久收入假设消费理论,建立中国农村居民消费的Panel Data模型,分析中国农村居民不同收入层次之间的消费差异,以及这种差异对农村居民消费结构的影响.结果表明:不同收入层次的农村居民的总消费支出差异显著,衣着消费模型为变截距模型,而居民食品、居住等其他消费支出差异不显著,模型表现形式一致,因此启动农村居民消费需求归根到底是要提高低收入层次居民的收入,拉动高收入层次居民的消费需求。     

Examination and prediction of fog and haze pollution using a Multi-variable Grey Model based on interval number sequences

In this study, a new Multivariable Grey Model (1,m) aimed at interval grey number sequences with known possibility functions is built using the kernel and degree of greyness under new definitions. Based on the new model, formulae are deduced to calculate and predict the upper and lower bounds of interval grey numbers. Since the grey system model and fog- and haze-prone weather have the same characteristics of uncertainty, this model was applied to simulate and predict the measurable indicators of fog and haze in Nanjing, China. We selected visibility data and particulate matter data with a diameter of 2.5 µm to build a new Multivariable Grey Model (1,2) with a new kernel and degree of greyness sequence. In addition, we established the traditional Multivariable Grey Model (1,2) with the original kernel and degree of greyness and the Auto-Regressive Integrated Moving Average Model (1,1,0). The results show that the new Multivariable Grey Model (1,2) has the best simulation and prediction effects among the three models, with average relative errors of simulation and prediction at 1.32% and 0.32%, respectively. To further verify the validity and feasibility of the proposed model, we added another real-world example to establish the three models mentioned above. The results prove that the proposed model has evidently superior performance to another two models.     

用灰色马尔柯夫链预测模型对我国粮食产量的预测

针对粮食生产的不确定性 ,本文提出了用建立在中心逼近式的 GM(1 ,1 )模型及马尔柯夫预测模型上的灰色马尔柯夫预测模型对我国粮食产量进行预测 ,预测建立在对过去年份的数据的分析之上 ,并给出了2 0 0 3年的粮食产量预测结果 .     

Preferences,income, and life satisfaction: An equivalence result

In this paper I investigate the nexus between life time utility (life satisfaction) and income predicted by the standard model of endogenous economic growth under different behavioral assumptions. The solution rationalizes why the empirical association between income and life satisfaction is approximately log-linear. I show that the solution is observationally equivalent when individuals compare their consumption (i) with others, (ii) with their own past consumption achievements, and (iii) not at all (ordinary preferences). This finding suggests that the observed slope of the income–life satisfaction curve is uninformative about the presence and strength of habits or reference-dependent utility.     

Retrospect and prospect of watershed hydrological model

IlltroductionIn the late 1950's, as the concept of watershed hydrological model emerged, researchersbegan to explore the integrated process of watershed hydrOlogical cycle as a system. ftoml960's to the midd1e of 1980's, several famous models were deve1oped. Since the late 1980's theadvance of new technologies, including RS, GIS, GPS, AI etc., has promoted the developmentof watershed modeling.This paPer reviews ConventionaJ Hydrological Models, Grey Hydrological Models and Dig-ital Hyd…     

Forecasting of foreign exchange rates of Taiwan’s major trading partners by novel nonlinear Grey Bernoulli model NGBM(1, 1)

The traditional Grey Model is easy to understand and simple to calculate, with satisfactory accuracy, but it is also lack of flexibility to adjust the model to acquire higher forecasting precision. This research studies feasibility and effectiveness of a novel Grey model together with the concept of the Bernoulli differential equation in ordinary differential equation. In this research, the author names this newly proposed model as Nonlinear Grey Bernoulli Model (NGBM). The NGBM is nonlinear differential equation with power index n. By controlling n, the curvature of the solution curve could be adjusted to fit the result of one time accumulated generating operation (1-AGO) of raw data. One extreme case from Grey system textbook is studied by NGBM, and two published articles are chosen for practical tests of NGBM. The results prove the novel NGBM is feasible and efficient. Finally, NGBM is used to forecast 2005 foreign exchange rates of twelve Taiwan major trading partners, including Taiwan.     

The short-run and long-run behaviour of personal consumption in Croatia

In this paper cointegration and error correction models are used to explore the long run and short run behavior of personal consumption in Croatia as a function of income, house prices and total credit to households. The results of the analysis showed that income (approximated by net real wage), house price and total credits to households play an important role in determining personal consumption. Also, lagged values of house prices showed significant impact on consumption, suggesting house price persistence. The most likely factors driving the house price persistence may include expectations and idiosyncratic institutional characteristics like illiquid real estate markets, inadequate property rights protection, high transaction costs, and underdeveloped financial instruments.     

陕西省城镇居民收入结构的灰色关联分析与趋势预测

应用灰色关联分析方法,分两个历史阶段对比研究了不同收入来源对陕西城镇居民人均可支配收入的影响,结果表明,居民收入结构不合理和发展不平衡现象较为严重,工薪收入和转移性收入是影响陕西居民收入的主要因素,并且其重要程度有进一步增强的趋势,其他来源的收入对居民收入增长有明显的抑制作用.最后,通过建立GM(1,1)新陈代谢模型群,对陕西城镇居民未来几年的人均可支配收入和工薪收入进行了预测.     

基于双风险因子调整的剩余收益经营与投资最优决策模型

一般来说,公司净资产基于投向可以分为净经营性资产和净金融性资产。这两种净资产所面临的风险属性是不同的,净经营性资产承担的是经营性风险,而净金融性资产承担的则是金融性风险。作为公司多元化经营的决策者,在公司净资产一定的情况下,如何合理分配经营性投资与金融性投资间的比例并作出最优的投资决策,以达到公司价值最大化？本文基于一般形式的三阶段剩余收益模型,根据净经营性资产具有经营风险,净金融性资产则具有金融风险的风险识别与判断,从理论上构建出双风险因子调整的剩余收益经营与投资决策模型(Operation and Investment Decision Model of Dual-risks RIM, OIDM-DRRIM)。同时,利用中国资本市场1997年到2014年的经验数据进行实证检验,研究结果表明,所构建的OIDM-DRRIM具有非常好的适用性,公司经营决策者可以根据该模型计算出净经营性资产和净金融性资产之间的最优分配比例,进而作出使公司价值最大化的经营与投资决策。