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将E变换的定义和其褶积求和用于水文离散系统线性概念模型的推导,以离散线性水库模型、离散Nash模型和离散Muskingum模型为例,阐述了求解步骤,较方便导出这些模型,同时给出了参数的求解. 相似文献
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《水电能源科学》2007,25(6):157-158
·水文水资源与环境·基于多嵌入维数的径流组合预测李红霞等1.1基于人工神经网络的长江三峡年最大洪峰流量长期预报孙树青等1.4水文离散系统矩估计的E变换张明1.8基于外部性消除的行政区水权交易方案设计严冬等1.10多指标半结构性模糊群决策评价方法李庆国等1.14深圳市水资源优化配置模型研究向波等1.17尼洋河流域水电梯级开发对生态环境质量影响的分析评价李朝霞1.21基于ArcGIS Server的WebGIS应用系统开发康玲等1.26基于ELMAN网络的河流健康复杂系统综合评价王伟等2.1防洪工程安全评价集对分析—可变模糊集模型赵吴静等2.5灰色自记… 相似文献
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Mellin变换在P-Ⅲ型分布参数估计中的应用 总被引:1,自引:1,他引:0
提出从Mellin变换理论出发,基于Mellin变换与矩间关系,给出了P-Ⅲ型分布参数估计方法,并与熵矩估计法相比.结果表明,理论结果与熵矩估计方法吻合,Mellin变换理论为准确矩估计提供了一种有效可行新的计算方法. 相似文献
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基于Mellin变换在概率权重矩法中的应用,建立了Mellin变换与概率权重矩、概率权重对数矩之间的关系,提出了一种概率权重混合矩法,以P-Ⅲ型分布参数估计为例进行分析。在此基础上,又提出了P-Ⅲ型分布参数估计的线性混合矩法。通过对云南省西南诸河10个水文站的年径流量观测资料拟合,表明概率权重混合矩法计算结果与概率权重矩法相当。 相似文献
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小流域洪水汇流参数适应性研究 总被引:2,自引:2,他引:0
洪水汇流参数(n,k)的率定是水文模型应用的一个主要问题.本文以径流形成原理为基础,利用矩与参数关系计算汇流参数,并对参数的合理取值接提出的约束条件估计,用实例验证其适应性. 相似文献
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以云南省10个水文站的年径流量观测资料为例,探讨了Mellin变换在指数Γ分布参数估计中的应用,提出了一种可变换获得P-Ⅲ型、Γ、K-M、P-V型分布等参数估计的积分变换矩法,并与指数Γ型分布参数估计矩法做了比较.结果表明,该方法较矩法实用、有效. 相似文献
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水文分析计算中两种正态变换方法的比较研究 总被引:4,自引:2,他引:4
采用Monte-Carlo统计试验方法对水文分析中常用的Box-Cox变换和多项式正态变换的统计性能进行了对比分析。以P-Ⅲ分布样本作为原始样本,采用参数检验和拟合分布检验方法比较了两种方法变换后样本的正态性,分析了反变换后对水文设计值的估计效果。研究表明,Box-Cox变换后样本的正态性更优,若以反变换后对水文设计值估计的统计性能评价。则以多项式正态变换的效果更优。 相似文献
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采用贝叶斯预报系统(BFS)水文不确定性处理器(HUP)对水文预报不确定性进行分析,实现概率洪水预报。以新安江流域水文模型为洪水预报模型提供流量初始预报系列,通过亚高斯模型对流量初始预报系列及实测系列分别进行正态分位数变换,由贝叶斯公式得到预报变量的后验概率分布并进行洪水过程的概率预报,采用分布点估值定值预报,并可通过构造置信区间对点估值预报的不确定性进行评估。以南一水库流域为例,将BFS后验概率分布均值与新安江模型预报进行对比,结果表明BFS可提高预报精度。 相似文献
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探讨了概率权重混合矩法在三参数对数正态分布、广义极值分布、广义帕雷托分布和广义逻辑斯特分布等参数估计中的应用,建立了概率权重混合矩与分布参数之间的数学关系,并以三参数对数正态分布为水文频率线型为例,对云南省西南诸河15个水文站年平均流量系列进行了拟合。结果表明,概率权重混合矩法估算精度与概率权重矩法大致相当。 相似文献
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This paper shows a general view of the renewable energy systems instaled in Mexico, since the early 70's up to the present date. Mention is made of the location, within the Mexican territory, of these systems, their power and the institutions that have participated in this program which are academic, federal government agencies, local government agencies as well as private companies. The installed systems are mainly: wind generators, flat and concentrator collectors, geothermal plants, biomass, solar ponds, photovoltaic systems and small hydrologic plants. 相似文献
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为了提高年径流量预测的精度,将灰色系统理论的弱化缓冲算子和人工神经网络相结合,提出一种新的年径流预测方法——引入灰色弱化缓冲算子的人工神经网络组合预测方法,并以兰州站年径流过程计算为例,验证了该方法的合理性。结果表明,预测结果精度较高,可见将引入灰色弱化缓冲算子的人工神经网络组合预测方法用于年径流预测具有可行性。 相似文献
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Effective stress is the primary control on permeability and thus on flow and water loss for two-well hot dry rock systems involving injection and production that have been tested to date. Theoretical relations are derived for the flow between an injector and producer, including the dependence of permeability on effective stress. Four relations for permeability as a function of effective stress are used to match field data for the hot dry rock systems at Rosemanowes, Cornwall, and Fenton Hill, New Mexico. The flow and water loss behavior of these systems are well explained by the influence of effective stress on permeability. All four relations for permeability as a function of effective stress are successful in matching the field data, but some have difficulty in determining unique values for elastic and hydrologic parameters. 相似文献
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采用IHA/RVA法和EFC指标分别分析澄碧河坝首站和平塘站的水文情势改变程度,并利用滑动平均法分析特殊水文指标的趋势。研究表明,澄碧河水文情势改变了河流生态,其中澄碧河坝首站、平塘站的水文综合改变度分别为46.04%、66.91%,均属中度改变;EFC的组成较变异前更为丰富;变异后,澄碧河坝首站、平塘站的1日最小流量分别以平均每年0.07m3/s的速率缓慢上升和平均每年0.01m3/s的速率缓慢下降。受水文情势和岩溶区的影响,上游平塘站对河流生态产生不利影响,下游坝首站更利于澄碧河枯水期河流生态的发展。研究结果为未来澄碧河实施生态监管提供了依据,建议加强监测和分析岩溶区流域水文气象要素,以保证河流生态健康安全。 相似文献
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《International Journal of Hydrogen Energy》2021,46(80):40022-40040
Plug-in hybrid fuel cell and battery propulsion systems appear promising for decarbonising transportation applications such as road vehicles and coastal ships. However, it is challenging to develop optimal or near-optimal energy management for these systems without exact knowledge of future load profiles. Although efforts have been made to develop strategies in a stochastic environment with discrete state space using Q-learning and Double Q-learning, such tabular reinforcement learning agents’ effectiveness is limited due to the state space resolution. This article aims to develop an improved energy management system using deep reinforcement learning to achieve enhanced cost-saving by extending discrete state parameters to be continuous. The improved energy management system is based upon the Double Deep Q-Network. Real-world collected stochastic load profiles are applied to train the Double Deep Q-Network for a coastal ferry. The results suggest that the Double Deep Q-Network acquired energy management strategy has achieved a further 5.5% cost reduction with a 93.8% decrease in training time, compared to that produced by the Double Q-learning agent in discrete state space without function approximations. In addition, this article also proposes an adaptive deep reinforcement learning energy management scheme for practical hybrid-electric propulsion systems operating in changing environments. 相似文献