Multi‐objective optimal design of FLC driven hybrid mass damper for seismically excited structures

Structural vibration control using active or passive control strategy is a viable technology for enhancing structural functionality and safety against natural hazards such as strong earthquakes and high wind gusts. Both the active and passive control systems have their limitations. The passive control system has limited capability to control the structural response whereas the active control system depends on external power. The power requirement for active control of civil engineering structures is usually quite high. Thus, a hybrid control system is a viable solution to alleviate some of the limitations. In this paper a multi‐objective optimal design of a hybrid control system for seismically excited building structures has been proposed. A tuned mass damper (TMD) and an active mass driver (AMD) have been used as the passive and active control components of the hybrid control system, respectively. A fuzzy logic controller (FLC) has been used to drive the AMD as the FLC has inherent robustness and ability to handle the non‐linearities and uncertainties. The genetic algorithm has been used for the optimization of the control system. Peak acceleration and displacement responses non‐dimensionalized with respect to the uncontrolled peak acceleration and displacement responses, respectively, have been used as the two objectives of the multi‐objective optimization problem. The proposed design approach for an optimum hybrid mass damper (HMD) system, driven by FLC has been demonstrated with the help of a numerical example. It is shown that the optimum values of the design parameters of the hybrid control system can be determined without specifying the modes to be controlled. The proposed FLC driven HMD has been found to be very effective for vibration control of seismically excited buildings in comparison with the available results for the same example structure but with a different optimal absorber. Copyright © 2002 John Wiley & Sons, Ltd.     

油气化探综合异常模糊划分动态聚类分级评价

通过选取描述油气化探综合异常的各种特征参量，借助模糊数学工具，利用最优聚类中心所具有的代表特征，建立分级指标，对油气化探综合进行分级评价。鄂尔多斯盆地油气化探综合异常的评价实例结果表明，利用油气化探综合异常各种特征参量进行动态聚类分级评价是可行的。     

冀鲁豫交界区地下流体模糊熵值的变化与地震的关系

采用概率化预处理方法，把冀鲁豫交界区地下流体多种观测项目的观测值转化为概率值时间序列，然后计算其模糊从属函数。在此基础上计算该区地下流体构成的信息源系统的模糊熵值，分析了模糊熵值变化与1983年山东菏泽Ms 5.9地震和1985年河北任县Ms5.0地震的关系。结果显示，在这两次中强地震前分别有明显的减熵异常过程，并且一次比一次明显，中强地震都发生在低熵值处，震后恢复到高熵值的变化过程。这可能反映了地下流体构成的信息源系统在地震孕育和发生过程中的减熵有序变化。通过研究认为，该区模糊熵值减到0.907为发震前兆异常警戒线，并且离中强地震发生的时间越近，减熵过程越大；震级越大，减熵过程越明显，减熵时间越长。     

干热风年型的模糊综合评判

根据武威１９８０—１９９７年春小麦产量和气候资料，利用模糊综合评判对干热风年型进行预测。预报效果好，实用性强。     

大震速报应用软件

大震速报应用软件和跃时孙文斌（中国黑龙江省１５７００９牡丹江地震台）概述近年来随着计算机的普及，许多台站配备了计算机。用其处理地震数据，并将结果经调制解调器，再经过电话线传输到北京，这对于决策部门指导抗震减灾工作有着重要意义。由此我们研制了一个可以在...     

Geostatistical regionalization of glacial aquitard thickness in northwestern Germany, based on fuzzy kriging

In many instances hydrogeological parameters obtained by conventional methods for selected localities within an aquifer or an aquitard are not sufficient for adequate regionalization at the scale of the entire layer. Here, we demonstrate an application of the fuzzy kriging method in regionalization of hydrogeological data, in which the set of conventional, crisp values is supplemented by imprecise information subjectively estimated by an expert. It is believed that such an approach eventually may reflect the real-world conditions more closely than a traditional crisp-value approach, because the former does not impose exactness artificially on phenomena which are diffuse by their nature. Spatial interpolation was done for the thickness of one of the major aquitards (till and glaciolacustrine clay) in northwestern Germany. The dataset consists of 329 crisp values from boreholes supplemented by 172 imprecise values defined as fuzzy numbers. It is demonstrated that the reliability of regionalization was higher, compared to regionalization performed with the crisp dataset only. Fuzzy kriging was performed with FUZZEKS (Fuzzy Evaluation and Kriging System) developed at the Ecosystem Research Center at the University of Kiel.     

Grade estimation using fuzzy- set algorithms

This paper presents a new approach for estimating unknown ore grades within a mining deposit in a fuzzy environment using fuzzy c- means clustering and a fuzzy inference system. Based on a collection of cluster centers obtained from fuzzy c- means, a fuzzy rule base and fuzzy search domains are established to compute grades at these cluster centers. These cluter center- grade pairs act as control information in the fuzzy space- grade system in order to infer unknown grades on the basis of fuzzy interpolation, fuzzy extrapolation, and a defuzzification process of fuzzy control.     

A Model-Based Approach to Semi-Automated Reconstruction of Buildings from Aerial Images

Automated reconstruction of building objects from aerial images is a complex problem due to the diversity of buildings as well as noise and low contrast of images, which are the results of distant photography, atmospheric effects and poor illumination. In this paper, a semi-automated approach to the reconstruction of parametric building models from aerial images is presented, which works with line segments extracted from the image. The model is selected interactively from a library of parametric models. A perceptual grouping technique is used to select the most significant image lines in terms of relations such as proximity and parallelism. Model lines are searched for the same relations as in the grouped image lines, and the corresponding lines undergo a matching procedure, which determines whether or not a match can be found between the given model and image lines. An experiment with aerial images of flat-roof and gable-roof buildings is shown and its results indicate the robustness and efficiency of the proposed approach.     

集成高度和彩色纹理特征的影像目标模糊聚类识别方法

提出一种基于高度和彩色纹理信息的目标识别方法 ,其目的是提取具有相对高度的地物。由于传统二维纹理分析的方法往往不能有效地提取这类目标 ,本文把高度、色彩和纹理信息有机地结合起来 ,提高了识别率。依据影像提取结果 ,探讨了树林对森林覆盖地区自动空中三角测量选点的负面影响 ,同时建议采用数据分组的方案来改善森林覆盖地区自动空中三角测量的精度 ,并用对比实验证明了其有效性。