Area aggregation in map generalisation by mixed-integer programming

Topographic databases normally contain areas of different land cover classes, commonly defining a planar partition, that is, gaps and overlaps are not allowed. When reducing the scale of such a database, some areas become too small for representation and need to be aggregated. This unintentionally but unavoidably results in changes of classes. In this article we present an optimisation method for the aggregation problem. This method aims to minimise changes of classes and to create compact shapes, subject to hard constraints ensuring aggregates of sufficient size for the target scale. To quantify class changes we apply a semantic distance measure. We give a graph theoretical problem formulation and prove that the problem is NP-hard, meaning that we cannot hope to find an efficient algorithm. Instead, we present a solution by mixed-integer programming that can be used to optimally solve small instances with existing optimisation software. In order to process large datasets, we introduce specialised heuristics that allow certain variables to be eliminated in advance and a problem instance to be decomposed into independent sub-instances. We tested our method for a dataset of the official German topographic database ATKIS with input scale 1:50,000 and output scale 1:250,000. For small instances, we compare results of this approach with optimal solutions that were obtained without heuristics. We compare results for large instances with those of an existing iterative algorithm and an alternative optimisation approach by simulated annealing. These tests allow us to conclude that, with the defined heuristics, our optimisation method yields high-quality results for large datasets in modest time.     

Detecting ethnic residential clusters using an optimisation clustering method

To understand residential clustering of contemporary immigrants and other ethnic minorities in urban areas, it is important to first identify where they are clustered. In recent years, increasing attention has been given to the use of local statistics as a tool for finding the location of racial/ethnic residential clusters. However, since many existing local statistics are primarily developed for epidemiological studies where clustering is associated with relatively rare events, its application in studies of residential segregation may not always yield satisfactory results. This article proposes an optimisation clustering method for delineating the boundaries of ethnic residential clusters. The proposed approach uses a modified greedy algorithm to find the most likely extent of clusters and employs total within-group absolute deviations as a clustering criterion. To demonstrate the effectiveness of the method, we applied it to a set of synthetic landscapes and to two empirical data sets in Auckland, New Zealand. The results show that the proposed method can detect ethnic residential clusters effectively and that it has potential for use in other disciplines as it offers an ability to detect large, arbitrarily shaped clusters.     

Reliability-based robust design for reinforcement of jointed rock slope

Traditional reliability-based design methodologies often involve selection of design which is of lowest cost and satisfies safety requirements. But, this design is sensitive to variation in statistics of input parameters (noise parameters) and might become unsatisfactory if an underestimation of coefficient of variation of input parameters is made. A relatively new design methodology known as robust geotechnical design (RGD) is applied for the case of reinforcement of rock slope using end-anchored rock bolts. This ensures selection of a cost-effective and safe design for which probability of failure (P_f) of reinforced rock slope is least sensitive to the noise parameters. Reliability-based RGD approach involves evaluation of P_f for each design with different possible noise parameters. Finding P_f for the complex geotechnical structure is computationally expensive, and thus an augmented radial basis function-based response surface is used as a surrogate to the finite element model of rock slope. This response surface, being very efficient, also performs well for a range of values of noise parameters. Later, minimum distance algorithm is applied to obtain a cost-effective and robust design. Finally, a comparison is made in the costs between two robust designs obtained for different target probability of failure for the same rock slope.     

Interpreting a Pareto set of operating options for water grids: a framework and case study

Multi-objective optimisation is being increasingly applied in water supply management to identify optimal operating options. However, a key challenge in the implementation of multi-objective optimisation is interpreting the large and multidimensional Pareto-optimal set. This paper shows how cluster, visual and post-optimisation analysis can aid the decision maker in addressing this challenge. This is demonstrated for a case study based on South East Queensland Water Grid, Australia, as part of a broader operational planning framework. Firstly, cluster analysis identifies a smaller set of representative options to aid in visual analysis. Secondly, visual analysis techniques are used to identify the trade-offs between objectives, the relationships between decision variables and objective performance, and to shortlist promising operating options. Finally, post-optimisation analysis techniques identify efficient operating options from the Pareto set, based on decision-maker preferences. Together these techniques can be used to identify a shortlist of operating options, for further consideration using multicriteria analysis.     

System Optimisation Of Multi-Beam Aperture Synthesis Arrays For Survey Performance

Investigating the requirements for an aperture synthesis array that optimise the performance for surveying shows that, next to collecting area and system temperature, the field-of-view (FoV) is key parameter. However, the effective sensitivity not only depends on bandwidth and integration time but could be seriously limited by side lobe confusion and by gain errors that determine the effective dynamic range. From the basic sensitivity equation for a radiometric system we derive an optimum cost ratio between collecting area and processing electronics, where the latter should be less than a third of the total cost. For an instrument that has to cover a fraction of sky larger than its field-of-view, the FoV enters the equation for survey sensitivity and we identify the number of independent feed systems per unit collecting area as a key parameter. Then the optimum cost distribution allows the electronics to account for up to half the total cost. Further analysis of the sensitivity formula shows that there is an optimum design frequency for a survey instrument below 1 GHz. We discuss the impact of station size and array configuration on self-calibration, side lobe confusion and effective sensitivity and conclude that a minimum station size of 20 m diameter is required at 0.3 GHz as long as multi-patch self-calibration procedures need, per baseline, a signal-to-noise ratio of more than two for each ionospheric coherence patch.     

New Challenges to Trajectory Design by the Use of Electric Propulsion and Other New Means of Wandering in the Solar System

The design of spacecraft trajectories is a crucial part of a space mission design. Often the mission goal is tightly related to the spacecraft trajectory. A geostationary orbit is indeed mandatory for a stationary equatorial position. Visiting a solar system planet implies that a proper trajectory is used to bring the spacecraft from Earth to the vicinity of the planet. The first planetary missions were based on conventional trajectories obtained with chemical engine rockets. The manoeuvres could be considered 'impulsive' and clear limitations to the possible missions were set by the energy required to reach certain orbits. The gravity-assist trajectories opened a new way of wandering through the solar system, by exploiting the gravitational field of some planets. The advent of other propulsion techniques, as electric or ion propulsion and solar sail, opened a new dimension to the planetary trajectory, while at the same time posing new challenges. These 'low thrust' propulsion techniques cannot be considered 'impulsive' anymore and require for their study mathematical techniques which are substantially different from before. The optimisation of such trajectories is also a new field of flight dynamics, which involves complex treatments especially in multi-revolution cases as in a lunar transfer trajectory. One advantage of these trajectories is that they allow to explore regions of space where different bodies gravitationally compete with each other. We can exploit therefore these gravitational perturbations to save fuel or reduce time of flight. The SMART-1 spacecraft, first European mission to the Moon, will test for the first time all these techniques. The paper is a summary report on various activities conducted by the project team in these areas.     

RGB-D SLAM在室内高精度三维测图中的应用

高精度三维测图是室内三维制图的重要支撑,基于三维激光雷达扫描技术的三维测图成本高,需要提前布置标靶,在室内复杂环境中易导致数据不完整;基于图像序列的三维重建建模时间长,易受多种因素影响。针对以上问题,本文将RGB-D SLAM技术应用于室内高精度三维测图中。通过将深度相机与SLAM技术相结合,计算相机位姿并恢复三维空间信息,获取室内三维点云模型,并以目标物实际量测为基准评价密集点云精度。试验结果表明,该方法可快速获取精度较高的三维点云模型,成本低且效率高,能够较好地满足应用需求。     

Calibration of a semi-distributed model for conjunctive simulation of surface and groundwater flows / Calage d’un modèle semi-distribué pour la simulation conjointe d’écoulements superficiels et souterrains

Abstract

Abstract A hydrological simulation model was developed for conjunctive representation of surface and groundwater processes. It comprises a conceptual soil moisture accounting module, based on an enhanced version of the Thornthwaite model for the soil moisture reservoir, a Darcian multi-cell groundwater flow module and a module for partitioning water abstractions among water resources. The resulting integrated scheme is highly flexible in the choice of time (i.e. monthly to daily) and space scales (catchment scale, aquifer scale). Model calibration involved successive phases of manual and automatic sessions. For the latter, an innovative optimization method called evolutionary annealing-simplex algorithm is devised. The objective function involves weighted goodness-of-fit criteria for multiple variables with different observation periods, as well as penalty terms for restricting unrealistic water storage trends and deviations from observed intermittency of spring flows. Checks of the unmeasured catchment responses through manually changing parameter bounds guided choosing final parameter sets. The model is applied to the particularly complex Boeoticos Kephisos basin, Greece, where it accurately reproduced the main basin response, i.e. the runoff at its outlet, and also other important components. Emphasis is put on the principle of parsimony which resulted in a computationally effective modelling. This is crucial since the model is to be integrated within a stochastic simulation framework.     

Strategy for consistent model parameter calibration for soft soils using multi-objective optimisation

Constitutive models for soft soils require a large number of parameters to model the complex material response. One set of parameters should capture the soil response for various laboratory & in situ stress paths. This requires a new method to calibrate a consistent set of model parameters using test data from different load paths of classic geomechanical tests. The feasibility of the proposed method is demonstrated with the recently developed CREEP-SCLAY1S model. After a sensitivity analysis that highlights the model parameters for optimisation, an optimisation process for two different configurations is designed. The latter is successfully verified against artificially generated laboratory data.