State-space ARIMA for supply-chain forecasting

ARIMA is seldom used in supply chains in practice. There are several reasons, not the least of which is the small sample size of available data, which restricts the usage of the model. Keeping in mind this restriction, we discuss in this paper a state-space ARIMA model with a single source of error and show how it can be efficiently used in the supply-chain context, especially in cases when only two seasonal cycles of data are available. We propose a new order selection algorithm for the model and compare its performance with the conventional ARIMA on real data. We show that the proposed model performs well in terms of both accuracy and computational time in comparison with other ARIMA implementations, which makes it efficient in the supply-chain context.     

Accuracy of wind energy forecasts in Great Britain and prospects for improvement

The metric representing the wind energy forecast error, when reported as a percent, is calculated quite differently than the error metrics for electricity transmission, electricity load, or in other industries such as manufacturing when they are also reported as a percent. The resulting calculated metric is quite different from what would be reported if the method utilized elsewhere was employed. This paper examines the possible forecast assessment and operational challenges associated with this finding. Concerning the prospects for improvement, the errors reported in MW of energy have a systematic component. With this insight, we developed a model to improve accuracy.     

基于降噪时序深度学习网络的风电功率短期预测方法

利用风电场历史功率数据预测未来一段时间内的风功率,对保障电网安全稳定运行具有重要的意义。本文提出一种基于奇异谱分析SSA(singular spectrum analysis)和长短时记忆LSTM(long-short term memory net⁃work)网络的时序特征预测框架用于短期风功率的预测。首先通过SSA对历史风功率原始数据进行降噪处理,然后经过数据转换之后,以LSTM网络为基础进行预测模型的训练,最后通过某风电场提供的两个风机的历史功率数据进行验证。实验结果表明,奇异谱分析对风电场的历史数据具有良好的降噪性,SSA+LSTM模型在测试数据上取得了较好的预测性能,能够有效进行短期风功率的预测。     

射孔完井出砂预测新模型及其在射孔优化中的应用

分析了射孔完井的油层出砂机理，以线弹性理论为基础，考虑变温应力和流体渗流作用的拖曳力影响，建立了一种新的射孔完井出砂预测模型。应用该模型研究射孔方位、射孔参数对油井出砂的影响，结果表明，深穿透射孔弹比大孔半径射孔弹能更好地避免孔道出砂，采用定向射孔能有效地减少油井出砂问题。其结果对砂岩油藏射孔优化设计具有一定指导意义。     

一种智能型的PCB产业需求预测方法

目前需求预测在整个印制电路板产业的生产活动控制中正扮演着越来越重要的角色。分析了影响印制电路板需求的因素和现有的预测方法,提出了一种适用于PCB产业需求预测的有效方法——遗传/BP—神经网络。实验表明该方法能够进一步改善印制电路板预测的准确度和减少生产成本的消耗。     

Logistic模型的改进及在油藏可采储量预测中的应用

为了更准确地预测油气藏未来的经济可采储量，依据油气藏随开发必然要经历产量递减和生产收支平衡的实际。利用Logistic模型中技术可采储量、产量与时间的相互关系，经推导和改进后，再结合当前经济技术条件下的废弃产油量，预测油气藏的有效生产时间及其经济可呆储量。实践证实，改进后的Logistic模型预测结果更符合油气藏的生产实际，能为油气藏的储量管理提供可靠的依据。     

多变量自回归模型在三江平原井灌水稻需水量预测中的应用

应用多变量自回归模型ARV(n), 利用三江平原腹地-富锦市1985～1999年气象资料, 按水稻生育期划分6个生育阶段, 建立了井灌水稻生育期内需水量预测模型. 经模型拟合与预测, 效果良好, 可以为该地区开展节水灌溉、灌溉用水管理、合理开发利用地下水资源, 缓解地下水危机提供参考依据.     

Investigation of the impact of changes in demand forecasting method on the financial performance of an electricity supply undertaking

Peak demand forecasts obtained from six different univariate forecasting methods, under a range of conditions, were used to drive a capacity acquisition model of a large electrical supply system; and the resulting physical and financial performance of the model was observed for each set of forecasts. The results obtained are discussed in the context of their implications for the choice of load forecasting method used in capacity acquisition planning by a power supply undertaking.     

台缙高速公路苍岭隧道水文地质勘察与涌水量预测

以台缙高速公路苍岭隧道为例，通过水文地质综合勘探方法，查明隧道不同裂隙发育程度岩体的渗透系数K值。然后利用地下水动力学法、地下水径流模数法对隧道开挖涌水量进行了预测。通过施工检验发现，涌水段位置和涌水量总体较接近，说明预测工作对隧道的施工开挖和排水设计具有指导意义。     

基于遗传算法的门限自回归模型在浅层地下水位预测中的应用

提出了建立门限自回归模型的一种简便通用的方法，用遗传算法可同时优化门限值和自回归系数．实例计算的结果说明了其可行性和有效性．该方法在各种工程时序预测中具有广泛的应用价值