混沌遗传算法在高层结构风振控制优化中的应用研究

将混沌遗传算法(Chaos Genetic Algorithm,简称CGA)引入高层结构的风振控制优化中,对采用黏弹性阻尼器来控制风振响应的高层结构进行参数优化;用Matlab语言编制了均布法、迭代法、简单遗传算法(Simple Genetic Algorithm,简称SGA)和混沌遗传算法的风振控制优化分析程序;对9个高层结构进行风振控制优化,对比了算法程序的计算效率以及无控、均布、迭代、SGA和CGA工况下的结构风振响应。研究结果表明:混沌遗传算法可以应用于高层结构风振控制优化之中;混沌遗传算法的计算效率比简单遗传算法最高提升了29%;经混沌遗传算法优化后,黏弹性阻尼器附加给结构的附加阻尼比与均布和迭代相比最高分别提高了61%和22%,CGA工况的顶层加速度响应与均布和迭代法相比最高分别减小了14%和12%。为高层结构风振控制优化研究提供了新思路,具有一定的理论价值和实际意义。     

岫岩MS5.4与海城MS7.3地震的共性和个性研究

1999年海城-岫岩交界地区的Ms5．4地震和1975年海城Ms7．3地震在许多方面有相似之处,如具有大量的前震和前兆异常。但由于两者震级不同,所以前兆异常既有共性,又有其特殊性。通过对这两次地震前地震活动特点及前兆异常的对比分析,利用数值模拟方法模拟了两次地震共性和个性可能的形成机制。     

基于遗传神经网络的入侵特征选择模型

针对高维数据包含的不相关和冗余特征影响检测方法性能的问题,提出了基于遗传神经网络入侵特征选择模型.该模型在传统的遗传神经网的输入层和隐含层之间增加特征选择层,并在特征选择层与输入层间设置连接开关,如果开关合上,则该特征被选中;否则为放弃.实验结果表明,该模型在保持原有信息完整性的同时,能有效减少冗余特性;在保证检测准确率的前提下,有效提高系统的检测速度.     

Estimation of monthly reference evapotranspiration using novel hybrid machine learning approaches

ABSTRACT

In this research, five hybrid novel machine learning approaches, artificial neural network (ANN)-embedded grey wolf optimizer (ANN-GWO), multi-verse optimizer (ANN-MVO), particle swarm optimizer (ANN-PSO), whale optimization algorithm (ANN-WOA) and ant lion optimizer (ANN-ALO), were applied for modelling monthly reference evapotranspiration (ET_o) at Ranichauri (India) and Dar El Beida (Algeria) stations. The estimates yielded by hybrid machine learning models were compared against three models, Valiantzas-1, 2 and 3 based on root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), Pearson correlation coefficient (PCC) and Willmott index (WI). The results of comparison show that the ANN-GWO-1 model with five input variables (T_min, T_max, RH, U_s, R_s) provides better estimates at both study stations (RMSE = 0.0592/0.0808, NSE = 0.9972/0.9956, PCC = 0.9986/0.9978, and WI = 0.9993/0.9989). Also, the adopted modelling strategy can build a truthful expert intelligent system for estimating the monthly ET_o at study stations.     

A conceptual evolutionary aseismic decision support framework for hospitals

In this paper, aconceptual evolutionary framework for aseismic decision support for hospitalsthat attempts to integrate a range of engineering and sociotechnical models is presented. Genetic algorithms are applied to find the optimal decision sets. A case study is completed to demonstrate how the frameworkmay applytoa specific hospital.The simulations show that the proposed evolutionary decision support framework is able to discover robust policy sets in either uncertain or fixed environments. The framework also qualitatively identifies some of the characteristicbehavior of the critical care organization. Thus, by utilizing the proposedframework, the decision makers are able to make more informed decisions, especially toenhance the seismic safety of the hospitals.     

GA-BP神经网络在罗源湾口波浪模拟研究中的应用

由于BP神经网络存在收敛速度慢和易于陷入极小值等缺点,引入遗传算法(GA)对网络的权值和阈值加以优化,并采用不同组合的输入因子和样本数,对福建省罗源湾口的波浪进行模拟研究.对输入因子的分析结果表明,研究区域的波浪主要受台湾海峡波浪传播影响,与局地气象因子(风速、风向、海气温差)的相关性较弱.训练样本试验表明,30 d以上的波浪历史数据可使GA-BP神经网络充分学习研究区域的波浪特征,从而实现对波浪要素的高精度模拟.模拟结果显示,对春、夏季实测波浪数据的模拟效果均很好,其中相关性分别为0.967和0.938,均方根误差分别为0.112 m和0.107 m,表明GA-BP神经网络在近岸波浪模拟预报中有较广阔的应用前景.     

A new approach to measurement of regional inequality in particular directions

Regional inequality is a core issue in geography,and it can be measured by several approaches and indexes.However,the global inequality measures can not reflect regional characteristics in terms of spatiality and non-mobility,as well as correctly explore regional inequality in particular directions.Although conventional between-group inequality indexes can measure the inequality in particular directions,they can not reflect the reversals of regional patterns and changes of within-group patterns.Therefore,we set forth a new approach to measure regional inequality in particular directions,which is applicable to geographic field.Based on grouping,we established a new index to measure regional inequality in particular directions named Particular Direction Inequality index(PDI index),which is comprised of between-group inequality of all data and between-group average gap.It can reflect regional spatiality and non-mobility,judge the main direction of regional inequality,and capture the changes and reversals of regional patterns.We used the PDI index to measure the changes of regional inequality from 1952 to 2009 in China.The results show that:1) the main direction of China’s regional inequality was between coastal areas and inland areas;the increasing extent of inequality between coastal areas and inland areas was higher than the global inequality;2) the PDI index can measure the between-region average gap,and is more sensitive to evolution of within-region patterns;3) the inequality between the northern China and the southern China has been decreasing from 1952 to 2009 and was reversed in 1994 and 1995.     

利用重测定的震源深度特征探讨2013年吉林前郭5.8级震群发震因素

利用Pn-Pg震相组合的局部搜索法,采用5种地壳速度模型对2013年吉林前郭5.8级地震震群进行震源深度测定。计算结果显示,5种结果的震源深度的主要分布特征相似。对选取的32个地震震源深度进行重新测定,结果最小为6 km,最大14 km,主要集中在10 km左右,系统深度偏差约1.74 km,震源深度分辨率约1.58km,重定位后地震震中优势分布呈北西向。与当地的沉积层厚度分布对比,这些地震最有可能发生在盆地基底的基岩顶层,而不在油气圈闭的沉积盖层内,并且地震震群分布走向与通榆—长春断裂走向相一致。结合该地区的历史地震活动与构造关系,最后推测这些地震与北西向的通榆—长春断裂构造运动密切相关,而不是油田作业的直接产物。     

Numerical correlation of speleothem stable isotope records using a genetic algorithm

The correlation of geological records is commonly based on subjective and arbitrary interpretation by a researcher. Geological data are usually collected as a series on a depth scale, and then chronologies of the profiles are constructed. The correlation of geological records based on matching quality indicators requires an efficient method of searching for the best position. GenCorr is a software based on a genetic algorithm, for correlation of records with or without accompanying chronological control. Where their age information is available, points on both records may be moved in the range limited by the age uncertainties. GenCorr has been developed by the authors in Borland RAD Studio 2007 environment. The authors tested the impact of matched record length, noise level, sampling resolution, or additional linear components and hiatuses on the correlation results using artificial test data. Finally, the genetic algorithm was applied to stable isotope records obtained from two stalagmites collected from the Demianova Cave System (Low Tatras, Slovakia). The results show that the genetic algorithm correlation method is similar to that used in pattern recognition by the human eye without prior knowledge of the ages. The genetic algorithm is able to correlate in multidimensional space and is free from human biases, but we accept that there are also occasions where additional expert opinion may be also important. GenCorr can be run on every PC with MS Windows operating system, the package was not tested in Mac environment. GenCorr is available as a freeware from the authors. For downloading, please contact: dzeq@twarda.pan.pl.     

Mining knowledge from result comparison between spatial clustering themes

This paper introduces some definitions and defines a set of calculating indexes to facilitate the research, and then presents an algorithm to complete the spatial clustering result comparison between different clustering themes. The research shows that some valuable spatial correlation patterns can be further found from the clustering result comparison with multi-themes, based on traditional spatial clustering as the first step. Those patterns can tell us what relations those themes have, and thus will help us have a deeper understanding of the studied spatial entities. An example is also given to demonstrate the principle and process of the method.