Knowledge discovery for geographical cellular automata

Recently, cellular automata (CA) has been increas-ingly applied to the simulation of geographical phe-nomena, especially urban simulation[1,2]. The re-searches of using CA have been carried out in China with many publications nationally and internation-ally[3―7]. CA can be applied to the simulation of many geographical phenomena, such as diffusion of wild-fire[8], population fluctuation of animals[9], evolution of urban systems and land use[1,2], the formation of idealized urban forms[3,6],…     

Integration of principal components analysis and cellular automata for spatial decisionmaking and urban simulation

This paper discusses the issues about the correlation of spatial variables during spatial decisionmaking using multicriteria evaluation (MCE) and cellular automata (CA). The correlation of spatial variables can cause the malfunction of MCE. In urban simulation, spatial factors often exhibit a high degree of correlation which is considered as an undesirable property for MCE. This study uses principal components analysis (PCA) to remove data redundancy among a large set of spatial variables and determine ‘ideal points’ for land development. PCA is integrated with cellular automata and geographical information systems (GIS) for the simulation of idealized urban forms for planning purposes.     

Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization

Abstract

Artificial neural networks (ANNs) have recently been used to predict the hydraulic head in well locations. In the present work, the particle swarm optimization (PSO) algorithm was used to train a feed-forward multi-layer ANN for the simulation of hydraulic head change at an observation well in the region of Agia, Chania, Greece. Three variants of the PSO algorithm were considered, the classic one with inertia weight improvement, PSO with time varying acceleration coefficients (PSO-TVAC) and global best PSO (GLBest-PSO). The best performance was achieved by GLBest-PSO when implemented using field data from the region of interest, providing improved training results compared to the back-propagation training algorithm. The trained ANN was subsequently used for mid-term prediction of the hydraulic head, as well as for the study of three climate change scenarios. Data time series were created using a stochastic weather generator, and the scenarios were examined for the period 2010–2020.

Editor Z.W. Kundzewicz; Associate editor L. See

Citation Tapoglou, E., Trichakis, I.C., Dokou, Z., Nikolos, I.K., and Karatzas, G.P., 2014. Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization. Hydrological Sciences Journal, 59(6), 1225–1239. http://dx.doi.org/10.1080/02626667.2013.838005     

断层结构非均匀性对地震活动性影响的细胞自动机模拟

基于断层强度分布的非均匀性,构建了由81×81个细胞单元组成的4种不同匀质度及其各自6种不同随机构型共计24个非均匀二维单断层模型样本,并通过设计的细胞自动机模拟程序,在保持其它模拟参数不变的条件下对它们进行了模拟试验．研究结果表明,随着断层结构非匀质度的增加,其宏观变形破坏行为由相对脆性向塑性变化;地震序列类型依次表现出主震型、前震-主震-余震型和震群型;震级分布表现出非均匀性依次减小; 地震发生在时间上表现为一种确定性的随机过程,即小震随机、中强地震丛集和大震准周期的特点．此外,结构几何分布的随机性也对地震序列的特点有较显著的影响,但这种随机差异性随着结构非匀质程度的增加逐渐减小．     

Development of operating rules for a complex multi-reservoir system by coupling genetic algorithms and network optimization

Abstract

An alternative procedure for assessment of reservoir Operation Rules (ORs) under drought situations is proposed. The definition of ORs for multi-reservoir water resources systems (WRSs) is a topic that has been widely studied by means of optimization and simulation techniques. A traditional approach is to link optimization methods with simulation models. Thus the objective here is to obtain drought ORs for a real and complex WRS: the Júcar River basin in Spain, in which one of the main issues is the resource allocation among agricultural demands in periods of drought. To deal with this problem, a method based on the combined use of genetic algorithms (GA) and network flow optimization (NFO) is presented. The GA used was PIKAIA, which has previously been used in other water resources related fields. This algorithm was linked to the SIMGES simulation model, a part of the AQUATOOL decision support system (DSS). Several tests were developed for defining the parameters of the GA. The optimization of various ORs was analysed with the objective of minimizing short-term and long-term water deficits. The results show that simple ORs produce similar results to more sophisticated ones. The usefulness of this approach in the assessment of ORs for complex multi-reservoir systems is demonstrated.

Citation Lerma, N., Paredes-Arquiola, J., Andreu, J., and Solera, A., 2013. Development of operating rules for a complex multi-reservoir system by coupling genetic algorithms and network optimization. Hydrological Sciences Journal, 58 (4), 797–812.     

Revisiting the 1669 Etnean eruptive crisis using a cellular automata model and implications for volcanic hazard in the Catania area

Cellular Automata provide an alternative approach to standard numerical methods for modelling some complex natural systems, the behaviour of which can be described in terms of local interactions of their constituent parts. SCIARA is a 2-D Cellular Automata model which simulates lava flows. It was tested on, validated by, and improved on several Etnean lava events such as the 1986–1987 eruption and the first and last phase of the 1991–1993 event. With respect to forecasting the surface covered by the lava flows, the best results were acceptable. The model has been used to determine hazard zones in the inhabited areas of Nicolosi, Pedara, S. Alfio and Zafferana (Sicily, Italy). The main goal of the current work in the Etnean area from Nicolosi to Catania has been the verification of the volcanic hazard effects of an eruptive crisis similar to the event that occurred in 1669. The simulation uses the volcanic data of the 1669 eruption with present-day morphology. Catania has been affected by some historical Etnean events, the most famous one being the 1669 eruption, involving 1 km³ of lava erupted over the course of 120 days. The simulation of ephemeral vents and the use of different histories within the experiments have been crucial in the determination of a new hazard area for Catania. In fact, during the simulation the city was never affected without the introduction of ephemeral vents, proving the fact that lava tubes played a fundamental role in the 1669 Catania lava crisis.     

Automatic extraction of geometrical characteristics hidden in ground‐penetrating radar sectional images using simultaneous perturbation artificial bee colony algorithm

Ground‐penetrating radar is one of the most effective methods of detecting shallow buried objects. Ground‐penetrating radar radargram is a vertical map of the radar pulse reflections that returns from subsurface objects, and in the case of cylindrical objects, it would be a hyperbola. In order to get clear and accurate information on the presence, location, and geometry of the buried objects, the radargrams need to be interpreted. Interpretation of the results is a time‐consuming task and needs an expert with vast knowledge. Development of an automatic interpretation method of B‐scan ground‐penetrating radar images would be an effective and efficient solution to this problem. A novel automatic interpretation method of ground‐penetrating radar images, based on simultaneous perturbation artificial bee colony algorithm using tournament selection strategy, simultaneous perturbation stochastic approximation method, and new search equations, is introduced in this paper. The proposed algorithm is used to extract geometrical parameters, i.e. depth, location, and radius, of buried cylindrical objects in order to assess its accuracy. Synthetic data, simulated using GprMax2D forward modelling program, and real data, surveyed in the campus of Isfahan University of Technology, are used in the assessment. The performance of the proposed method in detecting synthetic hyperbolas is compared with that of the original artificial bee colony algorithm, genetic algorithm, and modified Hough transform. The results show superiority of the proposed algorithm, in detecting synthetic hyperbolas. Furthermore, the performance of the proposed method in estimating depth and radius of pipes in real ground‐penetrating radar images is compared with that of the modified Hough transform. The results indicate higher accuracy of the proposed method in estimating geometrical parameters of the buried cylindrical objects.     

Optimal operation of reservoirs for downstream water quality control using linked simulation optimization

A methodology is developed for optimal operation of reservoirs to control water quality requirements at downstream locations. The physicochemical processes involved are incorporated using a numerical simulation model. This simulation model is then linked externally with an optimization algorithm. This linked simulation–optimization‐based methodology is used to obtain optimal reservoir operation policy. An elitist genetic algorithm is used as the optimization algorithm. This elitist‐genetic‐algorithm‐based linked simulation–optimization model is capable of evolving short‐term optimal operation strategies for controlling water quality downstream of a reservoir. The performance of the methodology developed is evaluated for an illustrative example problem. Different plausible scenarios of management are considered. The operation policies obtained are tested by simulating the resulting pollutant concentrations downstream of the reservoir. These performance evaluations consider various scenarios of inflow, permissible concentration limits, and a number of management periods. These evaluations establish the potential applicability of the developed methodology for optimal control of water quality downstream of a reservoir. Copyright © 2007 John Wiley & Sons, Ltd.     

Simulation of long‐term soil redistribution by tillage using a cellular automata model

The process of tillage translocation is well studied and can be described adequately by different existing models. Nevertheless, in complex environments with numerous obstacles, such as olive orchards, the application of conventional tillage erosion models is not straightforward. However, such obstacles have important effects on the spatial pattern of soil redistribution and on resulting soil properties. Cellular automata could provide a valuable alternative here. This study aims at developing a cellular automata model for tillage translocation (CATT) that can take into account such obstacles, exploring its possibilities and limitations. Firstly, model outcome was tested on a traditional field with rolling topography, for which caesium‐137 (¹³⁷Cs) inventories are available. The observed spatial soil redistribution patterns could be adequately represented by the CATT model. Secondly, a global sensitivity analysis was performed to explore the effect of input parameter uncertainty on several selected model outputs. The variance‐based extended Fourier Amplitude Sensitivity Test (FAST) method was used to determine first‐ and total‐order sensitivity indices. Tillage depth was identified as the input parameter that determined most of the output variance, followed respectively by tillage direction and speed. The high difference between the total‐ and first‐order sensitivity indices indicated that, in spite of the simple model structure, the model behaves non‐linearly with respect to some of the model output variables. Higher order interactions were especially important for determining the proportion of eroding and deposition cells. Finally, simulations were performed to analyse the model behaviour in complex landscapes, applying it to a field with protruding obstacles (representing olive trees). The model adequately represented some morphological features observed in actual olive orchards, such as mounds around the olive trees. The results show that cellular automata are an appropriate tool to describe long‐term tillage soil redistribution. Copyright © 2010 John Wiley & Sons, Ltd.     

A stochastic optimization framework for the restoration of an over-exploited aquifer

ABSTRACT

This study investigates the impact of hydraulic conductivity uncertainty on the sustainable management of the aquifer of Lake Karla, Greece, using the stochastic optimization approach. The lack of surface water resources in combination with the sharp increase in irrigation needs in the basin over the last 30 years have led to an unprecedented degradation of the aquifer. In addition, the lack of data regarding hydraulic conductivity in a heterogeneous aquifer leads to hydrogeologic uncertainty. This uncertainty has to be taken into consideration when developing the optimization procedure in order to achieve the aquifer’s sustainable management. Multiple Monte Carlo realizations of this spatially-distributed parameter are generated and groundwater flow is simulated for each one of them. The main goal of the sustainable management of the ‘depleted’ aquifer of Lake Karla is two-fold: to determine the optimum volume of renewable groundwater that can be extracted, while, at the same time, restoring its water table to a historic high level. A stochastic optimization problem is therefore formulated, based on the application of the optimization method for each of the aquifer’s multiple stochastic realizations in a future period. In order to carry out this stochastic optimization procedure, a modelling system consisting of a series of interlinked models was developed. The results show that the proposed stochastic optimization framework can be a very useful tool for estimating the impact of hydraulic conductivity uncertainty on the management strategies of a depleted aquifer restoration. They also prove that the optimization process is affected more by hydraulic conductivity uncertainty than the simulation process.

Editor Z.W. Kundzewicz; Guest editor S. Weijs     

滑坡表面位移无人机接触式监测的飞行路径优化——以三峡库区白水河滑坡为例

无人机监测技术发展迅速并开始广泛应用于滑坡监测领域之中,传统无人机监测通过拍摄影像对滑坡进行观测,存在着精确度方面的缺陷;引入无人机接触式监测方法到滑坡表面位移监测中,改善精度方面的不足,扩展其应用前景.目前无人机的续航问题是制约无人机监测技术发展的主要问题之一,无人机在滑坡上无序的飞行会增加飞行工作量,因此对无人机飞行路径优化十分重要.以三峡库区白水河滑坡为例,采用了蚁群算法对无人机在白水河滑坡上进行接触式监测时的飞行路径进行优化;结果表明:蚁群算法优化减少了无人机的飞行路径,大大提高了单次飞行效率.     

人工智能辅助规培医师对不同大小肺实性结节检出效能的初步研究

目的:探讨人工智能(AI)辅助检测软件对低年资规培医生提高肺实性结节检出效能的临床应用价值。方法:收集200例经CT证实有肺实性结节的CT影像,由2名8年影像诊断工作的主治医师结合AI(SCHOLAR,infervision)共同阅片确定肺实性结节数量,分歧时由第3名从事影像诊断15年以上主任医师会诊,最终确定"金标准"。先由低年资规培医师对上述CT图像独立进行肺结节检测(方法 A),2周洗脱期后在AI软件辅助下再进行上述CT图像肺结节检测(方法 B)。将方法 A和方法 B标注结果分别与"金标准"比较,记录真阳结节数、假阳结节数,采用SPSS 20.0数据统计软件比较两组间检测灵敏度、假阳性率差异,P <0.05为差异有统计学意义。结果:与方法 A相比,方法 B灵敏度明显增加,总的实性结节灵敏度提高65%,而假阳性率降低25%,差异有统计学意义(P <0.05);应用AI辅助软件对检测4组不同大小(D≤4 mm、4 mm 8 mm)肺实性结节的灵敏度均有提高,分别为78%、38%、27%和13.8%。方法 A...     

海洋平台结构振动的AMD主动控制参数优化分析

本文针对海洋平台结构的冰激振动和地震反应控制问题，提出了采用AMD主动控制的控制策略，结合JZ20－2MUQ平台结构进行了AMD控制系统的硬参数和软参数的优化分析，并就相应于最优参数下的AMD控制海洋平台结构冰激振动和地震反应的几种代表性工况进行了时程分析，得到了一些定性和定量的结论，为实际工程的控制设计提供了基础。本文提出的AMD主动控制方法对类似的海洋平台结构的控制问题也有参考价值。     

A hybrid optimization approach for efficient calibration of computationally intensive hydrological models

ABSTRACT

The calibration of hydrological models is formulated as a blackbox optimization problem where the only information available is the objective function value. Distributed hydrological models are generally computationally intensive, and their calibration may require several hours or days which can be an issue for many operational contexts. Different optimization algorithms have been developed over the years and exhibit different strengths when applied to the calibration of computationally intensive hydrological models. This paper shows how the dynamically dimensioned search (DDS) and the mesh adaptive direct search (MADS) algorithms can be combined to significantly reduce the computational time of calibrating distributed hydrological models while ensuring robustness and stability regarding the final objective function values. Five transitional features are described to adequately merge both algorithms. The hybrid approach is applied to the distributed and computationally intensive HYDROTEL model on three different river basins located in Québec (Canada).     

基于单台加速度记录的混合全局优化HVSR反演场地浅层速度结构

利用水平与竖向谱比（HVSR）方法反演场地速度结构是国际上迅速发展的研究领域.HVSR反演计算实质是一个土层场地模型空间搜索的全局优化问题,当模型搜索空间的复杂程度增大时,目前常用的搜索算法收敛速度慢,计算效率较低.本文实现了一种结合遗传和模拟退火方法优点的混合全局优化HVSR反演算法,通过理论模型和竖向台阵实测数据的检验,表明该算法能获得很好的反演效果,较好地解决了蒙特卡罗方法收敛速度慢,遗传算法收敛早熟和模拟退火算法搜索效率低的问题.本文在此基础上讨论了单台加速度S波记录用于场地速度结构HVSR反演的适用性,为基于单个地震台的地震观测记录反演浅层速度结构提供了一种高效且较为准确的反演方法.

     

井地电阻率法歧离率确定高阻油气藏边界

根据油气藏的特征,抽象出地球物理模型,利用有限元软件FEPG对三维油气藏模型的稳恒电流场进行了数值模拟.根据井地电阻率法计算结果,定义了一种新的参数歧离率,分析了不同深度油气藏和油气藏偏离钻井位置时歧离率的变化规律,并利用该参数及其梯度确定油气藏边界范围.理论分析表明,参数歧离率可很好地突出油气藏异常并确定其横向边界范围.     

基于纤维梁柱单元的桥梁墩柱地震反应模拟方法研究

为讨论利用纤维梁柱单元进行钢筋混凝土桥墩地震反应分析的建模方法,分别以4个悬臂式单柱墩和1个双柱墩拟静力加载试验,以及1个悬臂式单柱墩的振动台试验结果为依据,基于OpenSees数值分析平台建立了桥墩的地震反应分析模型。通过改变单元数量,分析了基于力的纤维梁柱单元和基于位移的纤维梁柱单元对桥墩地震反应的模拟精度。结果表明:对悬臂式单柱墩的拟静力和振动台试验,可沿墩高仅建立1个基于力的纤维梁柱单元,并在墩底串联1个考虑纵筋塑性渗透和粘结滑移的转动弹簧单元,即可获得很好的模拟结果。当采用基于位移的纤维梁柱单元时,应沿墩高至少建立2个单元,且塑性铰区至少有1个,才能保证获得较高的模拟精度。对双柱墩拟静力试验,采用基于力的纤维梁柱单元建模,沿每个墩高建立2个单元即可;以基于位移的纤维梁柱单元建模,建议沿每个墩高建立3个单元,且其中2个单元布置在塑性铰区。当数值模型可对静力滞回曲线取得很好的模拟结果后,该模型一般可对动力作用下墩顶最大位移和墩底最大剪力进行较为准确的模拟,但对墩顶残余位移的模拟精度无法保证。