大型抽水试验最优化设计研究

抽水试验最优化设计,是指针对一个具体的地下水系统优选出一个抽水试验设计,它使抽水试验的费用最小化,而试验所获资料能满足识别参数所要求的可靠性,它可以概化为一个非线性的混合整数规划问题,其决策变量是确定抽水井和观测井的位置及井数、抽水量和观测频率等,采用搜索算法求解了这一优化问题,得到了理论最优解,并进行了实例演算。     

遗传算法在非线性地下水经济管理模型中的应用

通常采用基于梯度的数学规划方法求解地下水管理模型,如线性规划和非线性规划。但对于高度非线性、非凸的优化问题,尤其是涉及到经济或环境的地下水管理模型,传统方法难以有效地寻找全局最优解。本文介绍了一种求解非线性地下水资源管理模型的遗传算法,并以山东羊庄盆地分布参数地下水系统非线性管理模型为例,给出了用遗传算法在求解这类问题的一般步骤。结果表明该方法能快速有效地找到全局最优解。     

Bjerhammar球面单层密度时间变化的实用解算理论

研究了Ｂｊｅｒｈａｍｍａｒ球面单层密度时变实用解算理论和稳定算法。从利用重复大地测量数据联合确定Ｂｊｅｒｈａｍｍａｒ球面单层密度时变基本理论出发,推导了不同Ｂｊｅｒｈａｍｍａｒ球面上ｑ＊ｔ和δＷ＊ｔ之间的一般解式;分析研究了ｑ＊ｔ的迭代求解过程和收敛特性,得出其收敛稳定性很大程度上取决于Ｒ值的结论,同时给出了界限Ｒ的关系式;提出了解求ｑ＊ｔ的分步迭代算法,该算法从理论上解决了以前算法存在的收敛稳定问题（Ｒ较小时）,并指出：地表观测点ｑｔ的确定应遵循匹配处理准则,即各观测点数据应蕴含相同物理过程。最后给出了ｑ＊ｔ的精度评估公式。     

Adaptive neuro-fuzzy inference system coupled with shuffled frog leaping algorithm for predicting river streamflow time series

ABSTRACT

Accurate runoff forecasting plays a key role in catchment water management and water resources system planning. To improve the prediction accuracy, one needs to strive to develop a reliable and accurate forecasting model for streamflow. In this study, the novel combination of the adaptive neuro-fuzzy inference system (ANFIS) model with the shuffled frog-leaping algorithm (SFLA) is proposed. Historical streamflow data of two different rivers were collected to examine the performance of the proposed model. To evaluate the performance of the proposed ANFIS-SFLA model, six different scenarios for the model input–output architecture were investigated. The results show that the proposed ANFIS-SFLA model (R² = 0.88; NS = 0.88; RMSE = 142.30 (m³/s); MAE = 88.94 (m³/s); MAPE = 35.19%) significantly improved the forecasting accuracy and outperformed the classic ANFIS model (R² = 0.83; NS = 0.83; RMSE = 167.81; MAE = 115.83 (m³/s); MAPE = 45.97%). The proposed model could be generalized and applied in different rivers worldwide.     

GM(1,1)模型的遗传算法优化及效果检验

对平稳的数据和非平稳数据两种数据序列建立的GM（1，1）模型，分别用加速遗传算法（AGA）和最小二乘法（LSM）对模型参数求解。结果表明：对平稳变化数据序列，两种方法建立的预测模型的拟合优度和预测精度无显著差异；对变化幅度较大的非平稳数据序列，基于AGA的GM（1，1）模型的拟合优度和预测精度高于基于LSM的GM（1，1）模型的拟合优度和预测精度。     

An algorithm for finding the position of a point relative to a fixed polygonal boundary

This article describes a method that determines the position of a point relative to a fixed boundary. Its advantage over the other existing algorithms described below is that in most cases it is necessary that only part of the algorithm be executed to determine the position of the point. A possible inconvenience of using this algorithm is that the contour boundary has to be entered as data. For problems where the boundary often changes the algorithm is not suitable in its present form. The applications envisaged here are to cases where the position of a very large number of points have to be determined relative to one fixed polygonal boundary whose shape is known in advance, for example, blanking out of contours in automatic contouring, or selecting drill holes which lie in the particular part of a mineral deposit.     

Structural physical parameter identification based on evolutionary-simplex algorithm and structural dynamic response

Evolutionary computation based on the idea of biologic evolution is one type of global optimization algorithm that uses self-adaptation, self-organization and random searching to solve optimization problems. The evolutionary-simplex algorithm is introduced in this paper. It contains floating encoding which combines the evolutionary computation and the simplex algorithm to ovcrcomc the problems encountered in the genetic algorithm and evolutionary strategy methods.Numerical cxpcrimcnts arc performed using seven typical functions to verify the algorithm. An inverse analysis method to identify structural physical parameters based on incomplete dynamic responses obtained from the analysis in the time domain is prcscntcd by using the evolutionary-simplex algorithm. The modal evolutionary-simplex algorithm converted from the time domain to the modal domain is proposed to improve the inverse efficiency. Numerical calculations for a 50-DOF system show that whcn compared with other methods, the evolutionary-simplex algorithm offers advantages of high precision,cfficient searching ability, strong ability to resist noise, independence of initial value, and good adaptation to incomplete information conditions.     

塔里木与扬子新元古代热-构造事件特征、序列和时代——扬子与塔里木连接(YZ-TAR)假设

淄博市大武水源地是中国北方罕见的特大型岩溶-裂隙地下水水源地,地下水开采量为52×10~4m~3/d。为了对岩溶地下水进行有效监测,需要建立最优的地下水监测网。文中在对岩溶地下水流系统分析的基础上,建立了地下水流系统确定性-随机性数学模型,运用有限元与卡尔曼滤波耦合的模拟递推算法,对大武水源地地下水监测网进行了优化设计,结果显示:现有地下水位动态监测网难以达到监测目标,最优地下水位监测网由14个监测井,每月监测一次的监测频率组成,比现有地下水位监测网减少了2个监测井。     

Improving the efficiency of ant algorithms using adaptive refinement: Application to storm water network design

The ant algorithm is a new evolutionary optimization method proposed for the solution of discrete combinatorial optimization problems. Many engineering optimization problems involve decision variables of continuous nature. Application of the ant algorithm to the optimization of these continuous problems requires discretization of the continuous search space, thereby reducing the underlying continuous problem to a discrete optimization problem. The level of discretization of the continuous search space, however, could present some problems. Generally, coarse discretization of the continuous design variables could adversely affect the quality of the final solution while finer discretization would enlarge the scale of the problem leading to higher computation cost and, occasionally, to low quality solutions. An adaptive refinement procedure is introduced in this paper as a remedy for the problem just outlined. The method is based on the idea of limiting the originally wide search space to a smaller one once a locally converged solution is obtained. The smaller search space is designed to contain the locally optimum solution at its center. The resulting search space is discretized and a completely new search is conducted to find a better solution. The procedure is continued until no improvement can be made by further refinement. The method is applied to a benchmark problem in storm water network design discipline and the results are compared with those of existing methods. The method is shown to be very effective and efficient regarding the optimality of the solution, and the convergence characteristics of the resulting ant algorithm. Furthermore, the method proves itself capable of finding an optimal, or near-optimal solution, independent of the discretization level and the size of the colony used.