Reservoir flood control operation based on chaotic particle swarm optimization algorithm

Reservoir flood control operation is a complex engineering optimization problem with a large number of constraints. In order to solve this problem, a chaotic particle swarm optimization (CPSO) algorithm based on the improved logistic map is presented, which uses the discharge flow process as the decision variables combined with the death penalty function. According to the principle of maximum eliminating flood peak, a novel flood control operation model has been established with the goal of minimum standard deviation of the discharge flow process. At the same time, a piecewise linear interpolation function (PLIF) is applied to deal with the constraints for solving objective function. The performance of the proposed model and method is evaluated on two typical floods of Three Gorges reservoir. In comparison with existing models and other algorithms, the proposed model and algorithm can generate better solutions with the minimal flood peak discharge and the maximal peak-clipping rate for reservoir flood control operation.     

城市防洪减灾决策方案优化研究

城市防洪减灾决策的成功与否直接影响着将来的洪水所造成的损失大小.如何应用自然、经济和社会信息,经超前分析以确保实施某一优化方案之后所造成的损失最小是防洪减灾决策的核心问题.本文深入地分析了城市防洪减灾决策方案优化的众多影响因素,在此基础上把模糊优选神经网络模型应用到城市防洪减灾方案优化中,并建立了城市防洪减灾方案优化模型,并通过实例验证了其有效性.     

A stochastic approach to the flood control problem

We propose a stochastic model in conjunction with reliability analysis concepts to improve estimates for the protection volume that should be allocated in a reservoir to control a flood wave. In this approach, the inflow that reaches the reservoir during a flood is considered to be a load, and the reservoir capacity to control this flood is considered to be the resistance that the reservoir offers against the propagation of the flood. Here, the load and the resistance are modeled as a diffusion stochastic process, and the protection volume is determined via Itô's formula. In this scenario, an explicit formula for the failure risk is derived. The parameter inference is carried out by a Bayesian approach for a time discrete version of the load, and the estimates are obtained by using Monte Carlo Markov Chain Algorithms (MCMC). The maximum likelihood estimators are used in the comparison. The record utilized comprises nine years of daily inflow rates during flood periods that come to the Chavantes hydroelectric power plant (CHPP) in Southeast Brazil. The protection volumes estimated through the proposed model are compared to the volumes obtained by other existing methods.     

基于两阶段混合整数规划模型的洪涝灾害应急管理研究

本文以洪涝自然灾害为现实背景, 考虑多种应急物资、灾情的不确定性和应急救灾的多目标性, 集成优化灾前准备和灾后响应两阶段, 建立了一定最大救援时间下的两阶段多目标混合整数规划模型。模型的目标一是使得不同灾害情景下灾后响应阶段总物资不足惩罚和延误损失的期望最小, 目标二是使得灾前准备阶段应急物资存储点建造成本、物资存储成本及灾后响应阶段物资分配成本之和最小。该模型保证了应急救灾的及时有效以及物资的公平分配。本文设计了一种多目标遗传算法用于模型求解, 结合具体算例, 得到了模型在最大救援时间为4到9区间内任意数值下的pareto最优解, 很好地适应了决策者不同的决策需求, 并根据pareto应急方案的数目, 灾后响应阶段成本期望和两阶段总成本等模型的三个关键产出随最大救援时间的变化趋势, 得出最优的最大救援时间为5.7。     

防洪风险分析中的一个二元标值犘狅犻狊狊狅狀点过程模型

该文将洪水的大小和持续时间作为防洪设施的工程风险中不可忽略的因素,提出了以洪水的大小和持续时间为标值的二元标值Ｐｏｉｓｓｏｎ点过程模型,给出了防洪综合风险率的计算公式,并进行了实例计算．     

Simulation-based collaborative decision support for surge floods prevention in St. Petersburg

The paper aims to implement a simulation-based collaborative decision support approach for flood control management in application to St. Petersburg surge floods, which are prevented by a complex of dams with several large openings. Despite the evolution of the numerical hydrodynamic models, hardware performance and computer technologies the accurate forecasting of storm surges and decision support for gates maneuvering is still an important issue. The prospective architecture and principal solutions of Flood Warning System with the emphasis on the simulation-based approach and collaborative decision support system on the basis of e-Science platform CLAVIRE are considered.     

An automated econometric decision support system: forecasts for foreign exchange trades

Making decisions challenges foreign exchange (FX) market brokers due to the volatility of the foreign exchange market, as well as the unmanageable flood of possibly relevant information. Thus, decision making in this complex and dynamically changing environment is a difficult task requiring automated decision support systems. In this contribution, we describe an econometric decision support approach, which enables the extraction of essential information indispensable to set up accurate forecasting models. Our approach is based on a genetic algorithm (GA) and applies the resulting models to forecast daily EUR/USD-exchange rates. In doing so, the genetic algorithm optimizes single-equation regression forecast models. The approach discussed is new in literature and, moreover, allows flexibility in automated model selection within a reasonably short time.     

Capacity Planning Model for a Multipurpose Water Reservoir with Target-Priority Operation

We consider the capacity determination problem of a hydro reservoir. The reservoir is to be used primarily for hydropower generation; however, commitments on release targets for irrigation as well as mitigation of downstream flood hazards are also secondary objectives. This paper is concerned with studying the complex interaction among various system reliabilities (power, flood, irrigation, etc.) and to provide decision makers a planning tool for further investigation. The main tool is an optimization model that recognizes the randomness in streamflow. The model incorporates a special target-priority policy according to given system reliabilities. Optimized values are then used in a simulation model to investigate the system behavior. Detailed computational results are provided.     

基于SPSS和Excel的三峡库区经济主成份分析方法研究

介绍了主成份分析的数学模型,并用于三峡库区区域经济指标分析,介绍基于统计分析软件SPSS和Excel进行经济分析的方法和步骤,为三峡库区区域经济分析提供一种具体的可行的计算机辅助决策分析方法.     

梯级水库群防洪系统多目标决策的灰色优选

将传统的优化技术与新发展起来的灰关联决策理论有机地结合起来,针对洪水调度的特点,提出了一个切实可行的梯级水库群洪水调度方案决策的灰色优选模型.最后,以乌江流域4个梯级电站的洪水调度方案优选进行了说明.     

基于区间二型梯形模糊集的应急物资储备动态协同决策模型

重大灾害下应急物资储备决策是阻止突发灾难蔓延的有效手段之一。针对救灾信息具备不确定性与复杂性特点,构建基于区间二型梯形模糊集的应急物资储备动态协同决策模型,并给出应急物资储备策略。利用区间二型模糊集理论的决策方案并结合比例分析法(COPRAS),构建常态环境下应急物资供应商选择的群决策模型,解决不相容群决策属性之间的冲突问题;进而,充分考虑“救灾阶段性动态时间因素”对储备决策的影响,构建动态救灾环境下应急物资储备结构模糊优化模型,实现常态决策与非常态应急决策之间的动态协同;最后,以2012年云南丽江“6.14”突发特大山洪灾害为实例进行数值分析,验证该动态协同决策模型的合理性与可行性,能有效解决动态救灾环境下应急物资储备结构优化问题。     

多状态系统的LAD决策树的建树方法研究

LAD( Logistic Data Analysis Tree)是一种逻辑数据分析技术 ,它将布尔代数和优化分析方法引入到了判别分析领域 ,提出了一种布尔变量集合的变量筛选和建模方法 ,并可以对冗余模式进行可视化识别与删除 .但目前的 LAD技术还仅限于二状态 ,而且算法复杂 .本文将 LAD决策树推广到了多状态情形 ,以三状态下建立 LAD决策树为例 ,提出了不可分辨度的定义 ,并以其下降最大作为寻找最优决策树的依据 .说明多状态下建立 LAD决策树的计算方法及重要的算法步骤 .最后 ,本文以鄱阳湖地区洪涝灾害影响研究为案例 ,采用 LAD决策树方法对其进行判别分析 .     

洪灾综合风险分析方法讨论(Ⅱ)——基于集对分析理论

对洪灾系统作综合风险研究,已是防洪减灾理论发展的一大趋势.在洪灾风险的同异反综合分析方法(概念模型)的基础上,以不确定性系数i对风险的影响为切入点,并进行适当的扩展与变换,将同异反综合分析方法进一步深入,建立了洪灾综合风险分析的模拟模型框架,初步得到了洪灾综合风险分析的可行途径.     

A group decision making model based on goal programming with fuzzy hierarchy: an application to regional forest planning

In this paper a multi-criteria group decision making model is presented in which there is a heterogeneity among the decision makers due to their different expertise and/or their different level of political control. The relative importance of the decision makers in the group is handled in a soft manner using fuzzy relations. We suppose that each decision maker has his/her preferred solution, obtained by applying any of the techniques of distance-based multi-objective programming [compromise, goal programming (GP), goal programming with fuzzy hierarchy, etc.]. These solutions are used as aspiration levels in a group GP model in which the differences between the unwanted deviations are interpreted in terms of the degree of achievement of the relative importance amongst the group members. In this way, a group GP model with fuzzy hierarchy (Group-GPFH) is constructed. The solution for this model is proposed as a collective decision. To show the applicability of our proposal, a regional forest planning problem is addressed. The objective is to determine tree species composition in order to improve the values achieved by Pan-European indicators for sustainable forest management. This problem involves stakeholders with competing interests and different preference schemes for the aforementioned indicators. The application of our proposal to this problem allows us to be able to comfortably address all these issues. The results obtained are consistent with the preferences of each stakeholder and their hierarchy within the group.     

防洪风险分析中改进的组合分布模型研究

洪水变量分布的选择是防洪风险分析中的一个重要工作 ,目前常用 P- 分布来描述洪水的随机特性 .建立在组合分布模型的基础上 ,本文提出了改进的组合分布模型 ,给出了不同情况下求最优分界点的模型 .实例计算表明 ,改进的组合分布模型在理论和应用上都优于原始分布 ,它能较好地反映洪水的风险     

基于破产理论的我国极端洪水保险风险组合随机优化模型

极端洪水给人类造成了巨大损失,极端洪水保险是分散极端洪水风险的一种有效手段.基于政府、市场和公众合作的极端洪水保险模式是适合我国国情的.在此模式下,建立政府有效参与的保险公司和保险区域风险组合随机优化模型,保证极端洪水保险的有效供给和需求,为合理厘定保险费率提供理论基础.随机优化模型中充分考虑了保险公司的破产概率、稳定性经营和保险区域的灾后恢复能力.最后给出了此模型的收敛性定理.     

Collaborative distributed decision making for large scale disaster relief operations: Drawing analogies from robust natural systems

One of the most ignored, but urgent and vital challenges confronting society today is the vulnerability of urban areas to extreme events. Current organization of response systems, predominantly based on a command and control model, limits their effectiveness and efficiency. Particularly, in decision‐making processes where a large number of actors may be involved. In this article, a new distributed collaborative decision‐making model is proposed to overcome command and control limitations encountered in stressful, hostile, chaotic, and large‐scale settings. This model was derived by borrowing concepts from the collective decision making of honeybees foraging, a successful process in solving complex tasks within complex settings. The model introduced in this article was evaluated through differential equations, i.e., continuous analysis, and difference equations, i.e., discrete analysis. The most important result found is that the best available option in any large‐scale decision‐making problem can be configured as an attractor, in a distributed and timely manner. We suggest that the proposed model has the potential to facilitate decision‐making processes in large‐scale settings. © 2005 Wiley Periodicals, Inc. Complexity 11:28–38, 2005     

火驱效果分析与综合评价

对火驱效果的认识与评价是火驱油藏管理的重要环节,评价过程需要火驱机理和监测数据相结合,但目前缺少对火驱项目效果客观认识的方法.针对这一问题,把火驱看做原油氧化和气驱增产的综合效果,利用油藏监测数据结合火驱机理对火驱效果进行深入分析,进而建立涉及动态增产指标和动态监测指标的综合评价模型,采用层次分析法确定各指标权重,应用模糊综合评价方法对火驱效果进行全面的评价.结果表明,火驱模糊综合评价结论客观地反映火驱的效果,避免了单因素评价的片面性,使火驱效果评价系统化,定量化.     

交汇、分流河道洪水演进模型及其应用

通过引入水深连接方程,耦合了干、支流河道的水流运动,给出了它们的流量分配关系,建立了交汇、分流河道洪水演进模型．对交汇河道中水流顶托作用随河道参数的变化规律进行了研究．分析了干、支流洪峰遭遇现象,指出干流和支流的洪峰遭遇是1998年长江大洪水干流高洪水位的重要原因之一．并定性解释长江干流荆江河段的裁弯取直和长江分流河道的淤积对河道水流的影响．     

A dynamic multi-objective optimization model with interactivity and uncertainty for real-time reservoir flood control operation

Despite the successes of both multi-objective optimization and uncertainty handling techniques in reservoir flood control operation, no work has been done yet on developing and investigating dynamic multi-objective optimization models for this problem. In this work, a dynamic multi-objective optimization model with interactivity and uncertainty was developed for the real-time reservoir flood control operation. Accordingly, a dynamic multi-objective optimization algorithmic framework with two newly designed change reaction strategies was proposed for solving the proposed dynamic model. Following the proposed algorithmic framework, any evolutionary multi-objective optimization algorithm can be converted into a dynamic optimizer. After investigating the difficulty variation of the proposed dynamic model, the effectiveness and robustness of the proposed algorithmic framework have been validated based on experiential studies on two typical floods of Ankang reservoir.