AP1000喷雾勺型件增压特性研究

本文利用STAR CCM+对AP1000喷雾勺型件增压特性进行模拟分析,给出不同喷雾流量下勺型件增压性能曲线,通过曲线拟合得到AP1000喷雾勺型件增压特性函数。将CFD模拟与工程计算结果对比,提出采用CFD分析结果优化工程计算的建议。     

Efficiency thresholds and cost structure in Senegal airports

This paper assesses airport efficiency levels in Senegal under a stochastic environment where the satisficing concept for different performance thresholds is applied. A two-stage satisficing DEA-Support Vector Machine approach is used here to compute the impacts of cost structure on these thresholds. In the first stage, within the ambit of the satisficing DEA model, the probabilities of achieving a minimal performance threshold are computed in a stochastic fashion. In the second stage, Support Vector Machine regression is used to discriminate between high/low efficiency groups within a given performance threshold. This methodology was sufficiently robust to handle small samples. The results reveal that the cost of capital and the cost of labor are the cost structure variables that have the greatest impact on efficiency levels, besides cargo operations.     

Land market,land development and urban spatial structure in Beijing

The paper first examines urban spatial patterns of the gradients of housing and land prices and land development intensity, and then tests the relationship between the land price gradient and housing price gradient. Urban theory predicts the former is steeper than the latter based on the notion of derived demand for land from the provision of housing services. Finally the paper examines the impact of the property of housing production function on urban spatial structure. For the property of housing production function, we are particularly interested in the elasticity of capital-land substitution. The paper concludes (1) market influences over spatial structure, (2) the derived demand for land, and (3) it is the actual (or expected) housing price increases that cause skyrocketing land prices, not the other way around.     

Gradient-based simulated maximum likelihood estimation for stochastic volatility models using characteristic functions

Parameter estimation and statistical inference are challenging problems for stochastic volatility (SV) models, especially those driven by pure jump Lévy processes. Maximum likelihood estimation (MLE) is usually preferred when a parametric statistical model is correctly specified, but traditional MLE implementation for SV models is computationally infeasible due to high dimensionality of the integral involved. To overcome this difficulty, we propose a gradient-based simulated MLE method under the hidden Markov structure for SV models, which covers those driven by pure jump Lévy processes. Gradient estimation using characteristic functions and sequential Monte Carlo in the simulation of the hidden states are implemented. Numerical experiments illustrate the efficiency of the proposed method.     

Using least squares support vector machines for the airframe structures manufacturing cost estimation

Accurate cost estimation plays a significant role in industrial product development and production. This research applied least squares support vector machines (LS-SVM) method solving the problem of estimating the manufacturing cost for airframe structural projects. This research evaluated the estimation performance using back-propagation neural networks and statistical regression analysis. In case studies, this research considered structural weight and manufacturing complexity as the main factors in determining the manufacturing labor hour. The test results verified that the LS-SVM model can provide accurate estimation performance and outperform other methods. This research provides a feasible solution for airframe manufacture industry.     

共轭梯度法优化设计低噪声FET放大器

本文利用放大器的噪声系数及增益表达式,构成目标函数,再利用共轭梯度和三次插值法进行计算机优化。用编制的优化程序AMAD设计、制作了一个S波段低噪声放大器,达到了较为满意的指标,较好地满足了系统组件的要求。     

Scheduling identical jobs on uniform parallel machines

We address the problem of scheduling n identical jobs on m uniform parallel machines to optimize scheduling criteria that are nondecreasing in the job completion times. It is well known that this can be formulated as a linear assignment problem, and subsequently solved in O ( n ³) time. We give a more concise formulation for minsum criteria, and show that general minmax criteria can be minimized in O ( n ²) time. We present faster algorithms, requiring only O ( n + m log m ) time for minimizing makespan and total completion time, O ( n log n ) time for minimizing total weighted completion time, maximum lateness, total tardiness and the weighted number of tardy jobs, and O ( n log² n ) time for maximum weighted tardiness. In the case of release dates, we propose an O ( n log n ) algorithm for minimizing makespan, and an O ( mn ^2m+1) time dynamic programming algorithm for minimizing total completion time.     

The Macro Process of the Regional Financial Development Gradient

金融已经成为地方经济发展的重要支撑条件,金融应该适应其生存的土壤才能获得更好的“成长”从而发挥最优作用。本文试图论证地方政府应该在中央政府的统一安排下根据不同地区的实际情况选择特色化的地区金融发展模式,才能促进地方金融与地方经济社会的良性互动与和谐发展以期为区域经济协调发展找到一条科学的金融解决路径。本文首先论证了区域金融差异梯度存在的逻辑是合理的,在此基础上分极化效应、扩展效应、回程效应三个方面系统论述了区域金融发展梯度差异演绎的宏观过程,并针对区域金融发展梯度推进中的市场机制与行政干预问题,认为区域金融发展梯度推进中虽然应该强调市场机制的作用,但适度的行政干预有利于优化金融发展路径。     

基于时间序列的支持向量机在物流预测中的应用

由于物流预测是不确定的、非线性的、动态开放性的复杂大系统，传统方法往往难以准确地描述这种复杂的非线性特征，因而无法准确进行物流预测，本文提出了基于一种基于时间序列的支持向量机(SVM)的物流预测方法。将该方法用于实际物流系统的公路运输量预测中，和真实值比较说明所提出的物流预测方法是可行和有效的。     

Interpretable sports team rating models based on the gradient descent algorithm

We introduce several new sports team rating models based on the gradient descent algorithm. More precisely, the models can be formulated by maximising the likelihood of match results observed using a single step of this optimisation heuristic. The proposed framework is inspired by the prominent Elo rating system, and yields an iterative version of ordinal logistic regression, as well as different variants of Poisson regression-based models. This construction makes the update equations easy to interpret, and adjusts ratings once new match results are observed. Thus, it naturally handles temporal changes in team strength. Moreover, a study of association football data indicates that the new models yield more accurate forecasts and are less computationally demanding than corresponding methods that jointly optimise the likelihood for the whole set of matches.