An adaptive compromise programming method for multi-objective path optimization

Network routing problems generally involve multiple objectives which may conflict one another. An effective way to solve such problems is to generate a set of Pareto-optimal solutions that is small enough to be handled by a decision maker and large enough to give an overview of all possible trade-offs among the conflicting objectives. To accomplish this, the present paper proposes an adaptive method based on compromise programming to assist decision makers in identifying Pareto-optimal paths, particularly for non-convex problems. This method can provide an unbiased approximation of the Pareto-optimal alternatives by adaptively changing the origin and direction of search in the objective space via the dynamic updating of the largest unexplored region till an appropriately structured Pareto front is captured. To demonstrate the efficacy of the proposed methodology, a case study is carried out for the transportation of dangerous goods in the road network of Hong Kong with the support of geographic information system. The experimental results confirm the effectiveness of the approach.     

A general framework for error analysis in measurement-based GIS Part 4: Error analysis in length and area measurements

This is the final of a series of four papers on the development of a general framework for error analysis in measurement-based geographic information systems (MBGIS). In this paper, we discuss the error analysis problems in length and area measurements under measurement error (ME) of the defining points. In line with the basic ME model constructed in Part 1 of this series, we formulate the ME models for length and area measurements. For length measurement and perimeter measurement, the approximate laws of error propagation are derived. For area measurement, the exact laws of error propagation are obtained under various conditions. An important result is that area measurement is distributed as a linear combination of independent non-central chi-square variables when the joint ME vectors of vertices coordinates are normal. In addition, we also give a necessary and sufficient condition under which the area measurement estimator is unbiased. As a comparison, the approximate law of error propagation in area measurement is also considered and its approximation is substantiated by numerical experiments.This project was supported by the earmarked grant CUHK 4362/00H of the Hong Kong Research grant Council.     

An Evaluation of Tropical Cyclone Genesis Forecast over the Western North Pacificand the South China Sea from the CMA-TRAMS

Tropical cyclone (TC) genesis forecasting is essential for daily operational practices during the typhoon season.The updated version of the Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS) offersforecasters reliable numerical weather prediction (NWP) products with improved configurations and fine resolution. Whiletraditional evaluation of typhoon forecasts has focused on track and intensity, the increasing accuracy of TC genesisforecasts calls for more comprehensive evaluation methods to assess the reliability of these predictions. This study aims toevaluate the effectiveness of the CMA-TRAMS for cyclogenesis forecasts over the western North Pacific and South ChinaSea. Based on previous research and typhoon observation data over five years, a set of localized, objective criteria has beenproposed. The analysis results indicate that the CMA-TRAMS demonstrated superiority in cyclogenesis forecasts, pre dicting 6 out of 22 TCs with a forecast lead time of up to 144 h. Additionally, over 80% of the total could be predicted 72 hin advance. The model also showed an average TC genesis position error of 218.3 km, comparable to the track errors ofoperational models according to the annual evaluation. The study also briefly investigated the forecast of Noul (2011). Theforecast field of the CMA-TRAMS depicted thermal and dynamical conditions that could trigger typhoon genesis, con sistent with the analysis field. The 96-hour forecast field of the CMA-TRAMS displayed a relatively organized three dimensional structure of the typhoon. These results can enhance understanding of the mechanism behind typhoon genesis,fine-tune model configurations and dynamical frameworks, and provide reliable forecasts for forecasters.     

扰动变量在强对流天气分析和模式评估中的应用——以苏北里下河地区引发龙卷的扰动系统为例

2016年6月23日14:00—15:00时,江苏省盐城市阜宁县发生了EF-4级有记录以来的强龙卷风过程,造成了当地30 km长,1.7 km宽的严重气象灾害。受局地环境影响,邻近地区在近50年中发生了大于10人次死亡事件的龙卷风11次,其中6次发生于1979年以后。文章首先是:(1)把6次事件日的再分析变量场分解成瞬时气候和扰动两个部分,发现6次事件都与近地面层出现的负高度扰动轴线和扰动冷暖气团的对峙有关,龙卷发生在暖气团一侧;(2)用模式初始场分解的扰动变量和扰动物理量评估欧美模式对产生阜宁龙卷扰动系统的预报能力。后者的结果也发现,当日14时925 hPa高度扰动槽和850 hPa扰动风辐合线作为环境扰动系统,以及湿涡度扰动和湿散度扰动等环境扰动指标量能够突出地表达有利于龙卷风发生的环境条件。欧洲全球模式能够提前42 h稳定预报出后来扰动槽和环境扰动指标量的位置,美国全球模式也可以提前18 h预报出这样的扰动特征。这些扰动变量和扰动指标量能够快速地帮助预报员判断有可能发生强对流天气的大致时空区域和特征。     

Probabilistic Model for Concentration Fluctuations in Compact-Source Plumes in an Urban Environment

A comprehensive model for the prediction of concentration fluctuations in plumes dispersing in the complex and highly disturbed wind flows in an urban environment is formulated. The mean flow and turbulence fields in the urban area are obtained using a Reynolds-averaged Navier-Stokes (RANS) flow model, while the standard k-ϵ turbulence model (k is the turbulence kinetic energy and ϵ is the viscous dissipation rate) is used to close the model. The RANS model provides a specification of the velocity statistics of the highly disturbed wind flow in the urban area, required for the solution of the transport equations for the mean concentration and concentration variance (both of which are formulated in the Eulerian framework). A physically-based formulation for the scalar dissipation time scale t _d , required for the closure of the transport equation for , is presented. This formulation relates t _d to an inner time scale corresponding to “internal” concentration fluctuation associated with relative dispersion, rather than an outer time scale associated with the entire portion of the fluctuation spectrum. The two lowest-order moments of concentration ( and ) are used to determine the parameters of a pre-chosen functional form for the concentration probability density function (clipped-gamma distribution). Results of detailed comparisons between a water-channel experiment of flow and dispersion in an idealized obstacle array and the model predictions for mean flow, turbulence kinetic energy, mean concentration, concentration variance, and concentration probability density function are presented.     

A Study of Concentration Fluctuations in Instantaneous Clouds Dispersing in the Atmospheric Surface Layer for Relative Turbulent Diffusion: Basic Descriptive Statistics

A series of tracer experiments studying the statistical properties of concentration fluctuations in clouds dispersing in the atmospheric surface layer is described and analyzed. Experiments were conducted at downwind fetches between about 200 and 1200 m, under a wide range of atmospheric conditions ranging from very unstable to moderately stable stratification. The present experiments have addressed basic requirements not met by past field experiments involving instantaneously released clouds; namely, the experiments provided repeat realizations of instantaneously released clouds measured with high-resolution concentration detectors, accompanied by the contemporaneous acquisition of high-quality meteorological and turbulence measurements.Extensive analyses are performed on the cloud concentration data in the framework of relative diffusion. Ensembles of cloud concentration realizations have been constructed. From these ensembles, crosswind and time profiles of the ensemble-mean concentration, concentration variance, ensemble-mean dosage, and dosage variance are obtained. The behaviour of the time profiles of the integral time scale of cloud concentration fluctuations is studied. The use of surface-layer similarity theory for the analysis of the downwind variation of a number of cloud quantities (e.g., cloud size and duration, cloud centre ensemble-mean concentration and dosage, cloud centre concentration and dosage variance, cloud centre integral time scale) is shown to be an effective basis for ordering these quantities. Furthermore, a number of approximate universal relationships describing the behavior of these cloud quantities has been derived. Finally, it is shown that the scaled crosswind and time profiles of ensemble-mean concentration and concentration variance as well as the scaled time profiles of the concentration fluctuation integral time scale exhibit self-similar forms that are independent of atmospheric stratification and downwind fetch.     

Numerical modelling of the turbulent flow developing within and over a 3-d building array,part iii: a istributed drag force approach,its implementation and application

A modified k- model is used for the simulation of the mean wind speed and turbulence for a neutrally-stratified flow through and over a building array, where the array is treated as a porous medium with the drag on the unresolved buildings in the array represented by a distributed momentum sink. More specifically, this model is based on time averaging the spatially averaged Navier–Stokes equation, in which the effects of the obstacle-atmosphere interaction are included through the introduction of a distributed mean-momentum sink (representing drag on the unresolved buildings in the array). In addition, closure of the time-averaged, spatially averaged Navier–Stokes equation requires two additional prognostic equations, namely one for the time-averaged resolved-scale kinetic energy of turbulence,, and another for its dissipation rate, . The performance of the proposed model and some simplified versions derived from it is compared with the spatially averaged, time-mean velocity and various spatially averaged Reynolds stresses diagnosed from a high-resolution computational fluid dynamics (CFD) simulation of the flow within and over an aligned array of sharp-edged cubes with a plan area density of 0.25. Four different methods for diagnosis of the drag coefficient C_Dfor the aligned cube array, required for the volumetric drag force representation of the cubes, are investigated here. We found that the model predictions for mean wind speed and turbulence in the building array were not sensitive to the differing treatments of the source and sink terms in the and equations (e.g., inclusion of only the `zeroth-order' approximation for the source/sink terms compared with inclusion of a higher-order approximation for the source/sink terms in the and equations), implying that the higher-order approximations of these source/sink terms did not offer any predictive advantage. A possible explanation for this is the utilization of the Boussinesq linear stress–strain constitutive relation within the k– modelling framework, whose implicit omission of any anisotropic eddy-viscosity effects renders it incapable of predicting any strong anisotropy of the turbulence field that might exist in the building array.     

Narratives in REDD+ benefit sharing: examining evidence within and beyond the forest sector

REDD+ was designed globally as a results-based instrument to incentivize emissions reduction from deforestation and forest degradation. Over 50 countries have developed strategies for REDD+, implemented pilot activities and/or set up forest monitoring and reporting structures, safeguard systems and benefit sharing mechanisms (BSMs), offering lessons on how particular ideas guide policy design. The implementation of REDD+ at national, sub-national and local levels required payments to filter through multiple governance structures and priorities. REDD+ was variously interpreted by different actors in different contexts to create legitimacy for certain policy agendas. Using an adapted 3E (effectiveness, efficiency, equity and legitimacy) lens, we examine four common narratives underlying REDD+ BSMs: (1) that results-based payment (RBP) is an effective and transparent approach to reducing deforestation and forest degradation; (2) that emphasis on co-benefits risks diluting carbon outcomes; (3) that directing REDD+ benefits predominantly to poor smallholders, forest communities and marginalized groups helps address equity; and (4) that social equity and gender concerns can be addressed by well-designed safeguards. This paper presents a structured examination of eleven BSMs from within and beyond the forest sector and analyses the evidence to variably support and challenge these narratives and their underlying assumptions to provide lessons for REDD+ BSM design. Our findings suggest that contextualizing the design of BSMs, and a reflexive approach to examining the underlying narratives justifying particular design features, is critical for achieving effectiveness, equity and legitimacy.

Key policy insights

• A results-based payment approach does not guarantee an effective REDD+; the contexts in which results are defined and agreed, along with conditions enabling social and political acceptance, are critical.

• A flexible and reflexive approach to designing a benefit-sharing mechanism that delivers emissions reductions at the same time as co-benefits can increase perceptions of equity and participation.

• Targeting REDD+ to smallholder communities is not by default equitable, if wider rights and responsibilities are not taken into account

• Safeguards cannot protect communities or society without addressing underlying power and gendered relations.

• The narratives and their underlying generic assumptions, if not critically examined, can lead to repeated failure of REDD+ policies and practices.

     

A rough set approach to the discovery of classification rules in spatial data

This paper proposes a novel rough set approach to discover classification rules in real‐valued spatial data in general and remotely sensed data in particular. A knowledge induction process is formulated to select optimal decision rules with a minimal set of features necessary and sufficient for a remote sensing classification task. The approach first converts a real‐valued or integer‐valued decision system into an interval‐valued information system. A knowledge induction procedure is then formulated to discover all classification rules hidden in the information system. Two real‐life applications are made to verify and substantiate the conceptual arguments. It demonstrates that the proposed approach can effectively discover in remotely sensed data the optimal spectral bands and optimal rule set for a classification task. It is also capable of unraveling critical spectral band(s) discerning certain classes. The framework paves the road for data mining in mixed spatial databases consisting of qualitative and quantitative data.     

Electro-Osmotic Consolidation Studies on Peat and Clayey Silt Using Electric Vertical Drain

Peat and soft soil deposits are abundant in Malaysia. Studies using electrokinetic geosynthetics (EKG) such as prefabricated electric vertical drains (EVD or ePVD) have shown the potential for the application of these materials in electrokinetic strengthening of soft clays and increasing solids content in mining tailings and sludges. There are no studies reported on the effectiveness of electro-osmosis using EVD in peat. Laboratory experiments were carried out to investigate the effectiveness of electro-osmotic stabilization of two peat samples and a slightly organic clayey silt sample, from the North Sarawak region. Commercially available EVD was used to induce electro-osmosis and drainage of pore water. The influence of voltage gradient, organic content, initial water content, anode–cathode configuration and presence of roots on electro-osmotic consolidation was investigated. Electro-osmotic consolidation using EVDs was effective in the improvement of peat, over a large range of initial water contents. An increase in the voltage gradient generally improved consolidation. The maximum voltage gradient for optimum results appeared to be in the region 120 V/m. The 2anodes-1cathode configuration performed better than the 1anode-1cathode configuration. The presence of roots reduced the electro-osmosis effect.