基于模糊神经网络的大场景人群密度估计方法 *

提出了一种估计大场景下密集人群密度的方法。该方法根据人类视觉的模糊性原理,认为用模糊集来划分人群密度范围比用确定的方法更符合人眼视知觉的认知方式,利用统计的方法确定灰度共生矩阵各指标对于各个密度类别的隶属函数;设计基于误差反向传播训练算法（BP）的模糊神经网络,计算样本模式对于各个密度类别的隶属度,并根据人群密度变化的时域连续性原理对人群密度范围进行合理估计。实验表明该方法提高了估计精度。     

A/O法废水处理碱源的研究与实践

从理论到实践阐述了以具有价格优势的 Na OH替代 Na2 CO3做碱源 ,解决 A / O法运行成本高的问题。     

论焊接结构生产的技术改造

本文讨论了焊接结构生产技术改造的有关问题，包括总思路及总目标、自动化的基本框架、按低成本自动化的原则设计生产线和关键技术问题的论述。     

初探混联法生产氧化铝的工艺优化

在目前的生产条件下。通过大量的混联法物料衡算，定量地研究了供矿铝硅比、熟料铝硅比和拜年法赤泥铝硅比对混联法的制造成本、能耗和拜年法与烧结法的生产比例的影响规律，提出我国混联法生产进一步优化的方向和途径。并开发了研究和评价的计算软件。为混联法的生产和设计的进一步优化奠定基础。     

基于贝叶斯的服务通告改装经济性决策方法

改装类服务通告的经济性决策是航空维修企业工程人员的一项重要工作内容。设计了改装类服务通告经济性决策程序;通过服务通告对飞机运营的经济性影响分析构建了成本分解结构,并对不同的成本项目建立了成本评估模型;针对模型的成本影响参数MTBUR和MTBF的估计采用了贝叶斯方法以解决小样本问题;通过投资回收期方法获得评价指标以决定是否进行服务通告改装投资。最后通过实例对决策方法的应用进行说明。此方法能够为航空企业的维修改装决策提供有效的技术支持。     

网络机房制冷效率研究

根据相关的调查显示,在传统观念和设计标准的影响下,网络机房存在各种各样的设计缺陷,其中的一些缺陷会导致网络机房内部空间形成热点、降低制冷容错能力、制冷效率和制冷量,从而提高运行成本。网络机房的制冷效率和运行成本的大幅提高成为制约发展的重要因素。文章从网络机房面临的实际问题出发,有针对性地分析了机房设计的典型错误,阐述了其原理和影响,并根据实践经验,介绍了一些简单可行的解决方案。     

Retrieving ocean surface current by 4-D variational assimilation of sea surface temperature images

In this article we propose a new method to estimate ocean mesoscale structures of the surface current velocity by processing sea surface satellite images. Assuming that the intensity level can be described by a transport-diffusion equation, the proposed approach is based on variational assimilation of image observations within a simple transport-diffusion model. This approach permits to retrieve the current velocity field from a sequence of satellite images. Results of processing synthetic data and real NOAA-AVHRR satellite images are presented and commented.     

Robust Kalman filtering for uncertain discrete-time systems with probabilistic parameters bounded within a polytope

We consider the problem of finite horizon discrete-time Kalman filtering for systems with parametric uncertainties. Specifically, we consider unknown but deterministic uncertainties where the uncertain parameters are assumed to lie in a convex polyhedron with uniform probability density. The condition and a procedure for the construction of a suboptimal filter that minimizes an expected error covariance over-bound are derived.     

Optimal experimental design and some related control problems

This paper traces the strong relations between experimental design and control, such as the use of optimal inputs to obtain precise parameter estimation in dynamical systems and the introduction of suitably designed perturbations in adaptive control. The mathematical background of optimal experimental design is briefly presented, and the role of experimental design in the asymptotic properties of estimators is emphasized. Although most of the paper concerns parametric models, some results are also presented for statistical learning and prediction with nonparametric models.