随机模糊神经网络模型预测铁水硅含量

该文在考虑了具有模糊化和非模糊化的模糊逻辑系统用于高炉铁水含硅量[Si]时各种噪声干扰的同时,把模糊数学理论和随机系统理论结合在一起,建立了一种新的高炉铁水含硅量[Si]的智能预报模型,该模型是由非单值模糊化、模糊规则库、模糊推理机、特殊非模糊化构成的随机模糊神经网络逻辑系统.通过结合莱钢1号高炉实时在线采集的生产数据,进行仿真研究,结果表明,该套模型能够很好地预测高炉铁水含硅量[Si].     

基于级联型组合分类器的人脸识别研究

该文提出了一种将支持向量机（SVM）与神经网络相结合的方法，得到一种新型的级联型组合分类器．此组合分类器先利用神经网络或SVM对人脸图像进行预分类，得到不同性别的两类人脸图像；然后分别针对其中某一类人脸图像进行K-I。变换以提取有效特征，再使用SVM进行细分，得到最终的识别结果．应用该组合分类器方法在本文整合得到的人脸样本库上进行测试，结果显示该方法不但可以有效地提高识别速度，而且还可以在一定程度上提高识别率，因此方法是有成效和有价值的．     

Prediction of the Indian summer monsoon using a stacked autoencoder and ensemble regression model

The study of climatic variables that govern the Indian summer monsoon has been widely explored. In this work, we use a non-linear deep learning-based feature reduction scheme for the discovery of skilful predictors for monsoon rainfall with climatic variables from various regions of the globe. We use a stacked autoencoder network along with two advanced machine learning techniques to forecast the Indian summer monsoon. We show that the predictors such as the sea surface temperature and zonal wind can predict the Indian summer monsoon one month ahead, whereas the sea level pressure can predict ten months before the season. Further, we also show that the predictors derived from a combination of climatic variables can outperform the predictors derived from an individual variable. The stacked autoencoder model with combined predictors of sea surface temperature and sea level pressure can predict the monsoon (June-September) two months ahead with a 2.8% error. The accuracy of the identified predictors is found to be superior to the state-of-the-art predictions of the Indian monsoon.     

基于复合战略控制系统的战略执行力研究

从控制理论的角度对战略控制系统与战略执行力的关系、传统战略控制系统进行了分析,在此基础上构建了基于复合战略控制系统的战略执行流程,为提高战略执行力提供了一种新思路。     

多国联合申报世界文化遗产模式的引入--以丝绸之路为例

近年来,我国世界文化遗产的申报取得了很大的成绩,很多珍贵的自然、人文遗产被列入世界文化遗产名录,受到全世界的共同关注与保护。但迄今为止,申报工作都是局限于我国范围内申报,尚未开展多国联合申报的尝试,模式比较单一。文章以丝绸之路为例,通过分析丝绸之路自身的特点,提出了多国联合申报世界文化遗产的设想,并进一步对中国引入多国申报模式的必要性作以初步的论述,以供学术界参考。     

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。     

两阶段订购模式下的供应链契约协调

本文针对短生命周期产品需求的不确定性,建立允许调整订货量的两阶段订货模型,由此得到销售商应该采取的最优订货量.在此基础上,运用契约协调机制,从而达到供应链的协调.     

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%.     

灰色预测算法在物流园区需求预测中的应用

对物流园区需求预测进行了系统分析,介绍了灰色预测算法,和物流园区腹地划分方法;结合连云港港口物流园区需求预测的实例进一步阐述了灰色预测算法在物流园区需求预测中的应用.     

油气勘探目标的经济评价

勘探目标经济评价要坚持常规经济评价和风险评价相结合，在用多种方法合理预测经济评价参数，充分考虑各种风险因素的基础上，认真做好风险评价研究，提高勘探目标经济评价的可靠性。