水库长期优化调度的可持续性模型初探

在水资源可持续利用思想指导下,建立了水库可持续长期优化调度模型.该模型以包含经济、社会、环境效益的综合效益最大化作为目标函数,在满足各种约束条件下协调当代与后代的用水需求.文中同时提出了分层模糊多目标动态规划法作为模型求解的一条途径.实例计算表明,该模型在一定程度上能够为水库可持续利用提供令人满意的决策方案.     

核磁测井数据弛豫谱反演软件研究

简单介绍了核磁测井数据弛豫谱反演方法原理 ,用混合编程方法和动态连接库技术 ,将用FORTRAN语言编写的核心处理模块转换为动态连接库 ,并在C++语言中动态调用。应用快速应用程序开发工具完成了图形用户界面的核磁测井数据处理软件设计。     

理论变异函数球状模型的加权线性规划法似合

对理论变异函数球状模型及其套合结构拟合这一问题作了探讨，提出了加权线性规划拟合法。同于该法在目标函数中既可考虑到对不同滞后h下所得实验变异函数值进行加权，又可保证拟合成功，同时还可进行人工干预，因此，方法综合了现有加权多项式拟合法及线性规划拟合法的各自优点，且在计算上较目标规划拟合法更为简单。     

目标规划方法在地下水资源管理中的应用

以满意决策理论为基础，针对地下水分布多数系统资源管理中关于建模和决策方面的某些突出问题，分析了用目标规划方法解决这些问题的基本思路，并结合某市水资源管理实例，讨论了目标规划方法的建模过程、求解方法、决策过程及其意义。     

非线性多含水层地下水越流系统水资源优化管理模型研究

提出了非线性多含水层地下水越流系统水资源管理的方法。内容包括非线性系统水资源管理的基本理论、算法原理、程序软件设计和理论检验，并把这一方法应用到唐山市以防治岩溶地面塌陷为目的的水资源管理中。     

新型钻井液用广谱护壁剂（GSP）的研究

ＧＳＰ系采用多种组份经特殊工艺化学合成的钻井液用防塌降失水剂，探讨了ＧＳＰ的合成及其作用机理，经测试和应用表明：ＧＳＰ高效多能，集降失水，防塌，润滑于一体，同时还兼有良好的保护油气层功能，使用简便，技术经济效益显著。     

CRM—PCIPS物化探数据图像处理系统的开发与实现

本对ＣＲＭ－ＰＣＩＰＳ物化探数据图像处理系统的需要分析、开发环境、系统结构、件系统、设计编码、程序调试与测试方法做了概括的介绍，并从“软件工程学”的角度对该项开发工作的进程，成功经验与不足之处进行了全面的评述。     

Air pollution hazard assessment using decision tree algorithms and bivariate probability cluster polar function: evaluating inter-correlation clusters of PM10 and other air pollutants

ABSTRACT

The automated classification of ambient air pollutants is an important task in air pollution hazard assessment and life quality research. In the current study, machine learning (ML) algorithms are used to identify the inter-correlation between dominant air pollution index (API) for PM10 percentile values and other major air pollutants in order to detect the vital pollutants’ clusters in ambient monitoring data around the study area. Two air quality stations, CA0016 and CA0054, were selected for this research due to their strategic locations. Non-linear RPart and Tree model of Decision Tree (DT) algorithm within the R programming environment were adopted for classification analysis. The pollutants’ respective significance to PM10 occurrence was evaluated using Random forest (RF) of DT algorithms and K means polar cluster function identified and grouped similar features, and also detected vital clusters in ambient monitoring data around the industrial areas. Results show increase in the number of clusters did not significantly alter results. PM10 generally shows a reduction in trend, especially in SW direction and an overall minimal reduction in the pollutants’ concentration in all directions is observed (less than 1). Fluctuations were observed in the behaviors of CO and NO_x during the day while NOx displayed relative stability. Results also show that a direct and positive linear relationship exists between the PM10 (target pollutant) and CO, SO₂, which suggests that these pollutants originate from the same sources. A semi-linear relationship is observed between the PM10 and others (O₃ and NO_x) while humidity shows a negative linearity with PM10. We conclude that most of the major pollutants show a positive trend toward the industrial areas in both stations while tra?c emissions dominate this site (CA0016) for CO and NOx. Potential applications of nuggets of information derived from these results in reducing air pollution and ensuring sustainability within the city are also discussed. Results from this study are expected to provide valuable information to decision makers to implement viable strategies capable of mitigating air pollution effects.     

顾及功能语义特征的建筑物空间分布模式识别方法

本文从空间-语义双重约束角度,提出一种顾及空间邻近和功能语义相似的建筑物空间分布模式识别方法。首先,基于建筑物的空间位置邻近性(即建筑物间的最小距离)约束进行聚类,获得建筑物的空间分布模式和建筑物间的空间邻近关系;然后,根据建筑物的功能语义相似性约束进行分割,获得建筑物的初步聚类结果;最后,考虑簇内相似性与簇间差异性进行整体优化,获得最终聚类结果。试验验证表明,本文方法比现有方法能够更有效地识别空间邻近与功能语义一致的建筑物群,服务于智慧城市建设中对建筑物进行语义层次综合和对城市结构进行深入研究的需求。     

Groundwater level simulation using gene expression programming and M5 model tree combined with wavelet transform

ABSTRACT

In order to understand and adequately manage hydrological stress, it is necessary to simulate groundwater levels accurately. In this research, gene expression programming (GEP) and M5 model tree (M5) are used to simulate monthly groundwater levels. The models are combined with wavelet transform to produce two hybrid models: wavelet gene expression programming (WGEP) and wavelet M5 model tree (WM5). For the simulation, groundwater level, temperature and precipitation values from three observation wells and one meteorological station, located in Iran, are used. The results indicate that the hybrid models, WGEP and WM5, lead to a better performance than the simple models, GEP and M5. The performance of the two hybrid models is similar. It is also observed that selecting a suitable time lag for inputs plays an important role in the accuracy of the simple models. The selection of a suitable decomposition level strongly affects the accuracy of hybrid models.