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.     

从关联分析法看如何改善沥青抗老化性能

用灰色关联分析法研究了沥青抗老化性能与沥青化学组成之间的关联程度，结果表明，影响再生沥青性质的主要因素是沥青中的芳烃和胶质的含量。通过添加芳香组分能改善沥青四组分之间的配伍性，从而可以改善再生沥青的抗老化性能。并通过对再生剂进行富芳处理，验证了上述结论。     

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     

Issues in nonlinear stochastic grey box identification

Grey box identification refers to the practice of identifying dynamical systems in model structures exploiting partial prior information. This contribution reviews a method for stochastic grey box identification and surveys experiences and lessons of applying it to a number of industrial processes. Issues to be addressed include advantages and costs of introducing stochastics into the model, the question of what contribution must be expected from the model designer as opposed to what can be formalized in computer algorithms, and an outlook on future plans to resolve present shortcomings.     

钢铁企业价格预测决策模型体系研究

通过对钢铁企业现行价格管理体系的分析 ,建立了钢铁企业价格预测决策模型体系。充分利用大量的定性、定量信息 ,并把趋势预测和因果预测技术相结合 ,采用组合预测模型对价格进行预测 ,最后对预测出来的多方案进行模糊综合评价 ,给出推荐方案顺序。实际应用表明 ,模型体系是有效的。     

A Search for Hidden Relationships: Data Mining with Genetic Algorithms

This paper presents an algorithm that permits the search for dependencies among sets of data (univariate or multivariate time-series, or cross-sectional observations). The procedure is modeled after genetic theories and Darwinian concepts, such as natural selection and survival of the fittest. It permits the discovery of equations of the data-generating process in symbolic form. The genetic algorithm that is described here uses parts of equations as building blocks to breed ever better formulas. Apart from furnishing a deeper understanding of the dynamics of a process, the method also permits global predictions and forecasts. The algorithm is successfully tested with artificial and with economic time-series and also with cross-sectional data on the performance and salaries of NBA players during the 94–95 season.     

Strategic appraisal of energy models for Mozambique

The needs that an energy supply system must meet are constantly changing, due to technological, social and political reasons. Effective energy planning is a dynamic process that is repeated periodically and adjusts to changing conditions. Energy decision makers and planners are no longer able to rely on inductive decision making since they have to investigate the effect of various decision parameters and possible future changes. To help in this process, models have been developed where estimates of future load growth, candidate power plants, fuels and other key factors can be introduced, from which the planners can evaluate decision parameters and the available alternatives. The paper presents the different methodologies and practices that are used by 11 energy models for energy demand forecasting, supply side management and generation expansion planning, demand side management and integrated resource planning. The paper concludes to the presentation of a strategic appraisal of the examined energy models appropriate for energy planning in Mozambique. Three models are proposed for conducting demand forecasting, generation expansion planning and demand side management. Copyright © 2002 John Wiley & Sons, Ltd.     

基于数学形态学的红外图像小目标检测

针对红外成像跟踪系统的低信噪比、背景和噪声干扰严重的小目标图像,以及后续的目标识别处理需要目标的灰度信息的特点,设计了一种基于数学形态学的红外灰度图像小目标检测算法,并用FPGA硬件实现。实验表明,数学形态学滤波能够大大提高目标的信噪比,去除背景和噪声干扰,保留目标的灰度信息,满足系统实时性要求,是一种有效的红外灰度图像小目标检测算法。     

非方程灰色系统方法在长期水文预报中的应用初探

基于水文过程的复杂性和影响因子信息收集不完善这一基本事实，本文将流域水文系统视为含有灰元和灰信息的灰色系统，并初步实践了非方程灰色预报方法在长期水文预报中的应用。方法在一定意义上脱离了传统的以方程为中心的预报模式，它既考虑预报因子对预报量的不同影响程度，又不过分强调预报量与预报因子的具体相关函数形式，为长期水文预报提供了一种新思路。文中列出了实例，效果令人满意。