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.     

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.     

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.     

进化策略算法在地面沉降量计算参数反演中的应用

多数情况下,评估的研究区缺乏多年积累的地下水位及开采量资料。因此,通常采用土力学模型,根据太沙基固结理论,进行地面沉降量预测。在地面沉降量计算中,土层变形参数值的选取直接影响计算结果的精确性。深层含水层埋深通常大于100m。通过现场勘探,采取土样进行岩土物理力学性质试验获取参数值,成本过于昂贵。通过参考区域土层物理力学性质资料,结合工程经验获取参数值,预测结果的精度得不到保证。针对上述情况,作者提出用非线性优化算法-进化策略算法,根据实测地面沉降量反演土层变形参数值。通过这种方法确定参数值,既节约成本,又保证了计算结果的可靠性。进化策略算法通过模拟生物遗传及进化过程,利用转移概率来帮助指导搜索。搜索结果不依赖于初始点的选择,对于求解全局最优解有很强的鲁棒性。作者将进化策略算法用于某一工程实例土层变形参数的反演,结果表明了该算法的可行性及稳健性,值得在工程实践中推广应用。     

一种改进的Delaunay三角化算法研究

Delaunay三角化在诸多应用领域具有极其广泛用途,也一直是计算机图形图像学和科学计算可视化技术的重要研究内容。针对二维约束Delaunay三角化问题,提出一种快速生成算法。该算法首先建立环形矩形,分环分治平面散乱点;然后依据Delaunay三角形的性质,从外环到内环分治逐步插入新点,一环插入完毕后,整理有效Delaunay三角形;依次循环快速生成二维约束Delaunay三角网格。本算法计算过程简单,计算效率高,程序编写十分容易无需复杂的递归过程,技巧性地解决了二维约束Delaunay三角化问题。实例证明,该算法具有较好的应用效果。     

改进的Prim算法在GIS中的应用

探讨了数字常平基础信息平台建设项目中构建一个低造价通信网的问题,建立了网络模型和相应的存储结构,采用优化的Prim算法实现了这颗最小生成树。     

基于遗传算法的叠前地震波形反演构建虚拟井曲线

叠前地震波形反演能够提供详细的地下地层特征，但由于其计算量大、数据和模型之间的非线性、目标函数的多极值和反演结果的多解性使叠前地震反演的实施成为一大难点。本文通过叠前和叠后混合反演技术采用遗传算法实现了深海无井地震反演。遗传算法思想简单、易于实现和使用、具有隐含并行性和全局搜索能力等优点，基于遗传算法的叠前地震波形反演得到了与井中实际数据基本吻合的速度和密度数据。