水泥土搅拌桩复合地基承载力的灰色预测

详细阐述灰色模型的建立及调整过程,利用复合地基沉降实测数据,根据灰色系统理论,建立(1,1)模型,可模拟复合地基的P~s曲线,预测地基沉降的发展趋势,分析水泥土搅拌桩复合地基的承载性能。     

面向售后服务的汽车备品需求预测研究

根据面向售后服务的汽车备品需求特点的差异,本文将其分为专用配件和通用配件并分别选用不同的预测模型.对专用配件,采用基于时间序列相关的线性回归模型,并运用加权最小二乘法（WLS）估计参数.对通用配件,选用GM（1,1）模型进行需求预测.     

区域物流需求量预测分析

区域物流需求量预测是政府有关部门制定物流规划和建设物流基地的决策依据，也是第三方物流企业发展物流业务的重要前提。本文在对区域需求量变化的影响因素分析以及对区域物流需求量指标选取的基础上．采用灰色预测方法对区域物流需求量进行预测。     

基于偏离度分析法的江苏省旅游就业潜力预测

当前，旅游业的就业功能受到广泛关注和普遍重视，预测和把握旅游就业潜力对促进一个国家和地区旅游业的发展乃至国民经济的发展意义重大。在借鉴已有相关研究成果的基础上，以江苏省为例，运用偏离度分析法对其旅游就业潜力进行了具体测算，以期对江苏省旅游就业工作的发展有所裨益。     

城市货运发展统计数据分析与建模

21世纪的物流在上海的经济活动中扮演着重要的角色,货运在城市交通中所占的比重日益增 加,如何科学地预测货运总量的发展趋势,对上海城市交通规划有着重要的意义。本文采用基于时间序列的 ARIMA模型,构建了上海货运总量发展模型,并对上海中短期的货运发展情况进行预测。     

趋势外推与ARMA组合的能源需求预测模型

能源需求预测是制定能源规划的重要组成部分.鉴于能源需求系统的复杂性和非线性特征,文章结合我国能源需求的历史数据,首先用趋势外推预测建立了单项预测模型,并对趋势外推预测的优缺点进行了分析;然后运用趋势外推与ARMA组合模型对趋势外推模型中的非趋势分量即残差序列进行分析,得到趋势外推与ARMA组合模型的预测结果;最后通过比较得出趋势外推与ARMA组合模型的预测结果不仅准确性高、而且稳定性好这一结论.这对于我国能源需求预测有着重要的理论意义和现实意义.     

An effective going concern prediction model for the sustainability of enterprises and capital market development

The purpose of this study is to construct a two-stage effective and innovative going concern prediction model to predict going concern doubt for the sustainability of enterprises and capital market development. Samples of this study are the companies listed on the Taiwan Stock Exchange or the Taipei Exchange, totalling 196 companies and including 49 companies with going concern doubt and 147 normal companies (with no going concern doubt). The data are taken from the Taiwan Economic Journal (TEJ) and the Market Observation Post System during the period from 2001 to 2016 (totalling 16 years). This study adopts a two-stage way to construct the going concern prediction models. In Stage I, the traditional statistical method of stepwise regression (SR) and the data mining technique artificial neural network (ANN) are applied to select the important variables. In Stage II, two decision tree algorithms (data mining techniques): classification and regression tree (CART) and C5.0 are used to establish the prediction models. The results show that the SR + CART model has the highest going concern prediction accuracy, with an overall accuracy of 87.42%.     

县(市)级土地利用总体规划中耕地需求量预测方法及其应用

科学准确地预测耕地需求量,是制定县(市)级土地利用总体规划的基础.文章根据中国南方某县1996-2005年来的耕地变更调查统计数据,分别采用趋势分析法、回归分析法、指数平滑法、GM(1,1)模型法和灰色-马尔柯夫链模型的方法,对该地区耕地总量进行了模拟和预测.不同方法的预测结果表明,基于灰色-马尔柯夫链方法的预测结果更加准确可靠,更有利于土地管理决策者的经济决策行为.在当前耕地利用方式的背景下,灰色-马尔柯夫链模型可以作为县(市)级土地利用总体规划中耕地需求量预测方法的一种好选择.     

ARIMA计量技术下河南省农民增收的预测模型研究

笔者根据河南省1978年～2005年的农民人均纯收入统计数据,将这些数据进行平稳化、零均值化处理,并利用时间序列的自相关函数,偏自相关函数的性质,确认数据所适合的模型.通过对样本数据所做的回归拟合模型定量分析,从而为河南省"十一·五"规划提供量化指标依据.     

Forecasting of electricity costs based on an enhanced gray-based learning model: A case study of renewable energy in Taiwan

This work presents a novel gray-based cost efficiency (GCE) model that integrates the gray forecasting model into a two-factor cost efficiency curve model for renewable energy (RE) technologies and identifies the optimal forecasting model for power generation cost of RE technologies. The analytical framework of proposed GCE model improves short-term prediction of power generation cost, and can be applied during the early developmental stages for RE technologies. Empirical analysis is based on wind power data for Taiwan. Time lag of knowledge stock was simulated to represent the actual relationship between R&D expenditures and cost reductions in power generation by knowledge stock. Analytical results demonstrate the GCE model is a useful tool to quantify the influences of cost reductions in power generation. The implications of analytical results are that institutional policy instruments play an important role in RE technologies achieving cost reductions and market adoption. The proposed GCE model can be applied to all high-technology cases, and particularly to RE technologies. The study concludes by outlining the limitations of the proposed GCE model and directions for further research.