复杂地表条件下共反射面元(CRS)叠加方法研究

在地表地形复杂的情况下,静校正不易做好,这是制约山地资料处理质量的一个很重要的因素.复杂地表共反射面元（CRS）叠加不需对叠前数据做静校正,而且在得到叠加剖面后可以利用叠加得到的波场参数剖面实现基准面重建.地震数据的试算表明,复杂地表CRS叠加得出的剖面与常规处理剖面相比有着较高的信噪比和同相轴连续性.与水平地表CRS叠加不同的是,在复杂地表CRS叠加的时距公式中,波场三参数耦合,难以通过简化CRS道集的方法将它们全部分离并逐个优化.引入模拟退火算法后,有效地解决了这一组合优化的难题.     

CNOP-P-based parameter sensitivity for double-gyre variation in ROMS with simulated annealing algorithm

Reducing the error of sensitive parameters by studying the parameters sensitivity can reduce the uncertainty of the model,while simulating double-gyre variation in Regional Ocean Modeling System(ROMS).Conditional Nonlinear Optimal Perturbation related to Parameter(CNOP-P)is an effective method of studying the parameters sensitivity,which represents a type of parameter error with maximum nonlinear development at the prediction time.Intelligent algorithms have been widely applied to solving Conditional Nonlinear Optimal Perturbation(CNOP).In the paper,we proposed an improved simulated annealing(SA)algorithm to solve CNOP-P to get the optimal parameters error,studied the sensitivity of the single parameter and the combination of multiple parameters and verified the effect of reducing the error of sensitive parameters on reducing the uncertainty of model simulation.Specifically,we firstly found the non-period oscillation of kinetic energy time series of double gyre variation,then extracted two transition periods,which are respectively from high energy to low energy and from low energy to high energy.For every transition period,three parameters,respectively wind amplitude(WD),viscosity coefficient(VC)and linear bottom drag coefficient(RDRG),were studied by CNOP-P solved with SA algorithm.Finally,for sensitive parameters,their effect on model simulation is verified.Experiments results showed that the sensitivity order is WD>VC>>RDRG,the effect of the combination of multiple sensitive parameters is greater than that of single parameter superposition and the reduction of error of sensitive parameters can effectively reduce model prediction error which confirmed the importance of sensitive parameters analysis.     

Effective medium theory and multiple linear regression-based velocity estimation in syn-rift clastic sequence of the Krishna–Godavari basin,India

An inclusion model, based on the Kuster–Toksöz effective medium theory along with Gassmann theory, is tested to forward model velocities for fluid-saturated rocks. A simulated annealing algorithm, along with the inclusion model, effectively inverts measured compressional velocity (V_P) to achieve an effective pore aspect ratio at each depth in a depth variant manner, continuously along with depth. Early Cretaceous syn-rift clastic sediments at two different depth intervals from two wells [well A (2160–2274 m) and well B (5222–5303 m)], in the Krishna–Godavari basin, India, are used for this study. Shear velocity (V_S) estimated using modelled pore aspect ratio offers a high correlation coefficient (>0.95 for both the wells) with measured data. The modelled pore aspect ratio distribution suggests the decrease in pore aspect ratio for the deeper interval, mainly due to increased effective vertical stress. The pore aspect ratio analysis in relation to total porosity and volume of clay reveals that the clay volume has insignificant influence in shaping the pore geometry in the studied intervals. An approach based on multiple linear regression method effectively predicts velocity as a linear function of total porosity, the volume of clay and the modelled pore-space aspect ratio of the rock. We achieved a significant match between measured and predicted velocities. The correlation coefficients between measured and modelled velocities are considerably high (approximately 0.85 and 0.8, for V_P and V_S, respectively). This process indicates the possible influence of pore geometry along with total porosity and volume of clay on velocity.     

模拟退火算法在室内定位中的应用

随着室内定位技术的广泛应用,如何高效、精准、低成本地实现室内定位尤为重要。本文分析了现有室内定位算法的不足,结合室内定位问题与模拟退火算法的特点,通过室内定位问题的数学抽象与建模,提出一种基于模拟退火算法的室内定位方法,给出了可行解邻域的选取方式与二范数的目标函数。实验结果表明该算法可实现高效、精准、低成本的定位效果,并且具有较好的鲁棒性和平差效果。     

SA算法优化BP神经网络应用于GPS高程拟合

BP神经网络算法用于高程拟合有训练速度慢和易于陷入局部最小值的缺点,基于BP算法学习特点,模拟退火算法（SA）在局部极小处的概率突变性,本文作者有效结合BP和SA算法,提出一种SA优化BP神经网络算法的BPSA混合学习策略,并以实例验证了该算法的有效性。     

Optimal pumping from skimming wells from the Yamuna River flood plain in north India

This report examines the problem involving the pumping of groundwater from a group of 90 existing wells along the banks of the Yamuna River, northwest of Delhi (India), underlain with geologically occurring saline water. It is known that unregulated pumping will lead to upconing of saline water and therefore it is necessary to determine optimal rates and associated well locations (from an existing group of candidate wells that supply drinking water to the city of Delhi) that will minimize the total salinity. The nonlinear, non-convex problem is solved by embedding the calibrated groundwater model within a simulation-optimisation (S/O) framework. Optimisation is accomplished by using simulated annealing (SA), a search algorithm. The computational burden is primarily managed by replacing the numerical model with a surrogate simulator-artificial neural network (ANN). The model is applied to the real system to determine the optimal pumping schedule. The results of the operational model suggest that the skimming wells must be operated from optimal locations such that they are staggered in space and time to obtain the least saline water.     

Multiobjective heuristic approaches to seismic design of steel frames with standard sections

Seismic design problem of a steel moment‐resisting frame is formulated as a multiobjective programming problem. The total structural (material) volume and the plastic dissipated energy at the collapse state against severe seismic motions are considered as performance measures. Geometrically nonlinear inelastic time‐history analysis is carried out against recorded ground motions that are incrementally scaled to reach the predefined collapse state. The frame members are chosen from the lists of the available standard sections. Simulated annealing (SA) and tabu search (TS), which are categorized as single‐point‐search heuristics, are applied to the multiobjective optimization problem. It is shown in the numerical examples that the frames that collapse with uniform interstorey drift ratios against various levels of ground motions can be obtained as a set of Pareto optimal solutions. Copyright © 2007 John Wiley & Sons, Ltd.     

复合形模拟退火算法及其在水泥土墙优化设计中的应用

将传统优化方法中的复合形法和智能优化方法中的模拟退火算法有机结合,得到一种新型的智能计算方法-复合形模拟退火算法。仿真分析表明它比单一的复合形法和模拟退火算法搜索性能更优。按照我国现行规范建立了水泥土墙优化设计数学模型,探讨了提出的复合形模拟退火算法在水泥土墙支护结构参数优化设计中的应用。给出了工程计算实例,其计算结果验证了方法的可行性和可靠性。还讨论了基坑内被动土压力区的加固对水泥土墙的嵌固深度和有效宽度的影响。     

遗传模拟退火算法在边坡稳定分析中的应用

利用遗传模拟退火算法结合瑞典圆弧法,寻找最危险滑裂面进行边坡稳定分析。对构造数学模型、确定计算步骤、选取参数等方面作了一定的研究。通过实例计算,结果令人满意。     

基于模拟退火算法的边坡稳定分析方法

岩石边坡开挖中存在大量的随机结构面,结构面与岩桥的组合破坏是边坡破坏的一种重要形式。如何确定抗剪强度最小的滑裂面是边坡工程中的重要研究方向。在岩体结构面调查统计基础上,运用随机网络模拟的方法得到边坡的裂隙网络图像,在此基础上应用模拟退火算法,搜索出边坡由结构面与岩桥组合形成的潜在最危险滑裂面的位置,将结构面组合滑动面与Sarma分析方法结合,形成一种改进的分析岩石边坡稳定性的方法--Sarma-SA分析法,通过一工程实例验证了该方法的合理性。