多维不确定性影响下的水期权交易最优策略研究

为解决来水预测不确定性和水价不确定性给用水户带来的风险对冲问题,引入对冲性的水期权交易模式,建立了以用水户期望收益最大为目标的水期权交易模型,得到了最优的期权交易策略应满足的条件,并利用二分法计算得到了最优的期权交易策略,探究了来水不确定性与水价不确定性对期权交易策略的影响。结果表明,来水预测误差和水价的波动越大,用水户的期望收益越大,最优的期权交易策略能有效降低来水预测不确定性和水价不确定性带来的风险。     

面向可解释性的物体拓扑结构骨架表征方法

目的 模式识别中，通常使用大量标注数据和有效的机器学习算法训练分类器应对不确定性问题。然而，这一过程缺乏知识表征和可解释性。认知心理学和实验心理学的研究表明，人类往往不使用代价如此巨大的机制，而是使用表征、归纳、推理、解释和约束传播等与符号主义人工智能方法类似的手段来应对物体识别中的不确定性并提供可解释性。因此本文旨在从传统的符号计算出发，利用骨架拓扑结构表征提供一种可解释性的思路。方法 以骨架树为基本手段来形成物体拓扑结构特征和几何特征的形式化表征，并基于泛化框架对少量同类表征进行知识抽取来形成关于物体类别的知识概括显式化表征。结果 在形成物体类别的概括表征实验中，通过路径重建直观展示了同类属物体上得到的最一般表征的几何物理意义。在可解释性验证实验中，通过跨数据的拓扑应用展示了新测试样本相对于概括表征的特定差异，表明该表征具有良好的可解释性。最后在形状补全的不确定性推理实验中，不仅可以得到识别结论，而且清晰展示了识别背后做出的判断依据，进一步验证了该表征的可解释性。结论 实验表明一般化的形式表征能够应对尺寸、颜色和形状等不确定性问题，本文方法避免了基于纹理特征所带来的不确定性，适用于任意基于基元的表征方式，具有更好的鲁棒性、普适性和可解释性，计算代价更小。     

Data‐driven model for river flood forecasting based on a Bayesian network approach

Uncertainty analysis of hydrological models often requires a large number of model runs, which can be time consuming and computationally intensive. In order to reduce the number of runs required for uncertainty prediction, Bayesian networks (BNs) are used to graphically represent conditional probability dependence between the set of variables characterizing a flood event. Bayesian networks (BNs) are relevant due to their capacity to handle uncertainty, combine statistical data and expertise and introduce evidences in real‐time flood forecasting. In the present study, a runoff–runoff model is considered. The discharge at a gauging station located is estimated at the outlet of a basin catchment based on discharge measurements at the gauging stations upstream. The BN model shows good performances in estimating the discharges at the basin outlet. Another application of the BN model is to be used as a reverse method. Knowing discharges values at the outlet of the basin, we can propagate back these values through the model to estimate discharges at upstream stations. This turns out to be a practical method to fill the missing data in streamflow records which are critical to the sustainable management of water and the development of hydrological models.     

基于多时间尺度和多源储能的综合能源系统能量协调优化调度

考虑源荷不确定性及储能设备配置对综合能源系统IES(integrated energy system)优化调度的影响,提出基于多时间尺度和多源储能的IES能量协调优化调度策略。该策略以系统运行经济最优、滚动控制时域内购能成本与储能惩罚成本之和最低以及设备输出功率调整量最小为目标,分别建立了日前、日内滚动和实时反馈3个时间尺度的优化调度模型。在日前考虑多种储能模式对IES经济性的影响;日内利用场景分析法描述滚动预测的不确定性来提高系统经济运行稳定性;再基于模型预测控制方法,构建日内与实时的反馈闭环优化,平抑由预测误差导致的系统功率波动。仿真结果表明:多源储能模式有助于提高IES的经济性;多时间尺度调度既可以保证IES运行的经济性,又能有效降低不确定性对系统实际运行的影响,减轻电网平抑功率波动负担。     

Shale gas pad development planning under price uncertainty

In this article, we study shale gas pad development under natural gas price uncertainty. We optimize the sequence of operations, gas curtailment, and storage on a single pad to maximize the net present value. The optimization problem is formulated as an mixed-integer linear programming model, which is similar to the one proposed by Ondeck et al. We investigate how natural gas price uncertainty affects the operation strategy in the pad development. Both two-stage and multistage stochastic programming are used as the mathematical framework to hedge against uncertainty. Our case study shows that there is value of using stochastic programming when the price variance is high. However, when the variance of the price is low, solving the stochastic programming problems does not create additional value compared with solving the deterministic problem.     

The price-setting newsvendor: review and extensions

The newsvendor problem is a staple of operations management research, pedagogy and practice. From its humble roots as a single-period problem for a price-taking newspaper seller, this problem (and its solutions) has inspired generations of researchers and students while contributing to inventory management at countless firms. One major extension of the newsvendor problem was the extension of the decision variables to include price as well as quantity. This extension has been known for decades, but recently gained new life, as researchers have expended considerable energy in analysing and exploring this scenario. We trace major developments in the single-period, price- and quantity-setting newsvendor problem in the recent past and propose extensions of these developments. We also extend a relatively unexplored model describing a price-setting newsvendor faced with a fixed stock level to show that there is a unique optimising price and that, as in the price- and quantity-setting newsvendor problem, the optimal price depends heavily on the form of the demand uncertainty.     

Using Exploratory Scenarios in Planning Practice

Abstract

Problem, research strategy, and findings: Despite growing interest by practitioners in using exploratory scenarios within urban planning practice, there are few detailed guidelines for how to do this. Through the discussion of five case examples, we illustrate different approaches to linking exploratory scenarios to different planning contexts. We conclude by observing that to directly inform a plan, regardless of the specific approach taken, exploratory scenarios in urban planning must incorporate stakeholder values and not only rely on expert judgment and analysis.

Takeaway for practice: Exploratory scenarios are effective for analyzing uncertainty within a planning process. However, exploratory scenarios can be incorporated into planning practice in different ways, ranging from workshops among experts that aim to cultivate general learning to complex projects that result in highly detailed scenarios and recommendations for plans. Practitioners can draw on the cases we present to inspire planning methods for particular projects, taking into account specific contexts and goals.     

A multiobjective integrated multiproject scheduling and multiskilled workforce assignment model considering learning effect under uncertainty

Today, organizations try to decline academically expenses using humans and resources in addition to rising managers and operators' satisfaction. Meantime, a very important step in the process of decision is the assignment of human resources, particularly in connection with research and development (R&D) projects in which the system is highly dependent on the capabilities of human resources. In this study, we tried all the assumptions that come true in the real world, considered a model for applied R&D projects to reduce costs and increase the efficiency of projects. Therefore, an integrated multiproject scheduling and multiskill human resource assignment model under uncertainty has developed for R&D projects. Furthermore, it is assumed that the activity processing time is related to human resources assignment that means the learning effect is considered. To demonstrate the proposed model efficiency, the various dimensions instance problem was solved accurately and efficiently in GAMS software, and the results have been reported. In addition, the proposed model is validated through the input parameter sensitivity analysis. The results indicate a suitable performance of the proposed fuzzy mathematical programming model is due to the complexity of the problem.     

An extended stochastic pseudo-spectral Galerkin finite element method (XS-PS-GFEM) for elliptic equations with hybrid uncertainties

Nouy and Clement introduced the stochastic extended finite element method to solve linear elasticity problem defined on random domain. The material properties and boundary conditions were assumed to be deterministic. In this work, we extend this framework to account for multiple independent input uncertainties, namely, material, geometry, and external force uncertainties. The stochastic field is represented using the polynomial chaos expansion. The challenge in numerical integration over multidimensional probabilistic space is addressed using the pseudo-spectral Galerkin method. Thereafter, a sensitivity analysis based on Sobol indices using the derived stochastic extended Finite Element Method solution is presented. The efficiency and accuracy of the proposed novel framework against conventional Monte Carlo methods is elucidated in detail for a few one and two dimensional problems.     

高效液相色谱法测定Fapas能力验证样品中咖啡因含量的不确定度评定

目的评定高效液相色谱法测定Fapas能力验证项目中咖啡因含量的不确定度。方法依据国家计量技术规范JJF1059.1-2012《测量不确定度评定与表示》对研磨咖啡粉(Sample A)和去咖啡因研磨咖啡粉(Sample B)2个样品中咖啡因含量测定的不确定度来源进行分析。通过建立数学模型量化不确定度分量,计算合成不确定度和扩展不确定度,并与Fapas能力验证结果进行对比。结果 Sample A结果报告为(13.36±0.21) g/kg,k=2; Sample B结果报告为(265.0±5.1) mg/kg,k=2,且Fapas能力验证结果为满意; 2个样品咖啡因含量测量不确定度均主要来源于标准曲线配制过程、样品重复性和标准曲线拟合3部分。结论该研究可为评价咖啡因含量测定结果的质量和控制实验室内部质量提供参考;同时不确定度评定和能力验证结果表明实验室在不同的浓度水平上均有能力开展相关检测并能保证数据可靠。