杆板结构系统的可靠性分析

提出一种可模拟飞行器翼面等薄壁结构的杆板结构系统的可靠性分析方法，导出在Ｍｉｓｅｓ屈服条件下平面应力元件的完全裕量方程。     

关于丢番图方程 x~3 ± 512 = Dy~2

用初等方法研究了丢番图方程ｘ３±５１２＝Ｄｙ２，并给出了无非平凡整数解的充分性条件．     

Modeling users through an expert system and a neural network

With the number of Internet and Web users increasing rapidly, electronic service providers are competing to satisfy and better serve customers looking for information or channels of advertisement. A wide variety of browses, specialized sites, custom made software, etc. are being offered on a regular basis. However, the user has to filter through a large number of files before finding what he/she is really looking for. This paper presents a user modeling expert system, SIGMA, based on neural networks for encapsulating Internet and Web users' habits and preferences. SIGMA is an artificial intelligence application designed to answer an Internet client needs and preferences. It analyses the user supplied demographic data and the monitored transactions then generate a tailored profile that is ultimately used to filter what information is being passed on to him/her in an effort to reduce and hopefully eliminate the time and energy expended in sifting through raw and often unwanted data.     

Simulation based on learning methods

The use of simulation technology as a tool for planning and control is of increasing significance in most fields of production. The main part of the expenditure concerning simulation analyses is the modelling of the considered production. Despite the use of modern building-block-oriented modelling technology, this modelling can often not be done by the user, but only by external experts. Against this backdrop, an adaptive simulation system is being developed by the Institute for Industrial Manufacturing and Management (IFF) at the University of Stuttgart. It independently adapts to real production processes, i.e. it learns about the interdependencies of production processes, and, in this way, supports the user in constructing and maintaining the model. In terms of information technology, the research in the field of artificial intelligence, especially in the subdomain of machine learning, is the basis for the realization of such adaptive systems.     

Bayesian Landmark Learning for Mobile Robot Localization

To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optimality, since they rely on a human to determine what aspects of the sensor data to use in localization (e.g., what landmarks to use). This paper describes a learning algorithm, called BaLL, that enables mobile robots to learn what features/landmarks are best suited for localization, and also to train artificial neural networks for extracting them from the sensor data. A rigorous Bayesian analysis of probabilistic localization is presented, which produces a rational argument for evaluating features, for selecting them optimally, and for training the networks that approximate the optimal solution. In a systematic experimental study, BaLL outperforms two other recent approaches to mobile robot localization.     

有关行为主义人工智能研究综述

通过与传统人工智能的比较，介绍了基于行为的智能模拟技术的发展及现状，并详细评述了行为主义人工智能的研究方向以及在研究过程中涉及到的前沿技术，最后给出了基于行为主义人工智能构建智能主体系统的设计原则。     

Boundary Layers in an Ocean Related System

In this article two regularizations of an hyperbolic model system derived from the primitive equations of the ocean (or the atmosphere) are presented. The two regularized systems converge to different limits as the regularization parameter converges to 0. Numerical approximations of these equations and numerical simulations are also presented     

The Calculation Model for Operation Cost of Coal Resources Development Based on ANN

On the basis of analysis and selection of factors influencing operation cost of coal resources development, fuzzy set method and artificial neural network (ANN) were adopted to set up the classification analysis model of coal resources. The collected samples were classified by using this model. Meanwhile, the pattern recognition model for classifying of the coal resources was built according to the factors influencing operation cost. Based on the results achieved above, in the light of the theory of information diffusion, the calculation model for operation cost of coal resources development has been presented and applied in practice, showing that these models are reasonable.     

基于FLANN的动态称重法

根据“逆模型”的思想 ,利用神经元网络良好的逼近能力 ,基于函数联接型神经网络 ( FLANN)的传感器动态补偿方法和最小二乘法 ,提出了一种车辆动态称重解决新方法     

理论研究方法在膜超(微)滤研究中的应用

在对超(微)滤的过滤性能及过程的研究中，实验研究作出了很多贡献，但实验研究存在着结论对具体实验体系有很大依赖性、研究费用较高等缺点．介绍几种较经典的扩散模型和流体动力学模型及其建模思路、适用范围和存在问题；提出借助理论分析和计算方法设计实验，再根据实验数据利用人工神经网络建立普用性模型的新方法、对于方程的求解，介绍了简化法、摄动法、数值计算与模拟等方法的特点及其在超(微)滤研究中的应用，认为用数值计算的方法研究超(微)滤机理及膜器优化设计必将成为今后超(微)滤研究的重要方向之一．