中国城市房价、收入与房价收入比的时空分异格局

中国城市房价快速增长背景下,城市房价、收入与房价收入比空间格局既有相似性,也表现出差异性,其空间异质性与空间依赖性特征显著。本文以中国337个地级行政单元为研究对象,运用泰尔指数、位序-规模和空间马尔科夫链等方法,对2009—2018年中国城市房价、收入和房价收入比的时空分异格局、整体稳定性和空间依赖性特征进行分析发现:(1)中国城市房价增长呈现出波动性特征,整体分异程度增强,房价城市体系呈现"金字塔型"结构,收入则表现出平稳增长态势,整体分异度降低,城市体系呈现"橄榄型"结构,在房价与收入共同影响下,房价收入比整体差异性显著加强;(2)城市房价空间格局表现出"地带性"与"等级性"差异并存,而收入更多表现出"地带性"差异,房价收入比则以"等级性"差异为主;(3)城市房价和收入类型的稳定性和空间依赖性较强,高、低水平城市存在两极分化与"俱乐部收敛"现象,房价收入比稳定性相对较弱。对中国城市房价、收入和房价收入比时空分异格局和空间关联效应的分析,可以为探索中国城市房价收入比空间分异模式与机理提供必要研究基础。     

线性MX链上的Peierls二聚化

从Ｂａｅｒｉｓｗｙｌ－Ｂｉｓｈｏｐ模型出发，研究了Ｍ离子（过渡金属离子）或Ｘ离子（卤素离子）的晶格位移对ＭＸ链的Ｐｅｉｅｒｌｓ二聚化的物理效应。结果表明，Ｘ离子较之于Ｍ离子更易于发生二聚化     

Mining transition rules of cellular automata for simulating urban expansion by using the deep learning techniques

Along with the gradually accelerated urbanization process, simulating and predicting the future pattern of the city is of great importance to the prediction and prevention of some environmental, economic and urban issues. Previous studies have generally integrated traditional machine learning with cellular automaton (CA) models to simulate urban development. Nevertheless, difficulties still exist in the process of obtaining more accurate results with CA models; such difficulties are mainly due to the insufficient consideration of neighborhood effects during urban transition rule mining. In this paper, we used an effective deep learning method, named convolution neural network for united mining (UMCNN), to solve the problem. UMCNN has substantial potential to get neighborhood information from its receptive field. Thus, a novel CA model coupled with UMCNN and Markov chain was designed to improve the performance of simulating urban expansion processes. Choosing the Pearl River Delta of China as the study area, we excavate the driving factors and the transformational relations revealed by the urban land-use patterns in 2000, 2005 and 2010 and further simulate the urban expansion status in 2020 and 2030. Additionally, three traditional machine-learning-based CA models (LR, ANN and RFA) are built to attest the practicality of the proposed model. In the comparison, the proposed method reaches the highest simulation accuracy and landscape index similarity. The predicted urban expansion results reveal that the economy will continue to be the primary factor in the study area from 2010 to 2030. The proposed model can serve as guidance in urban planning and government decision-making.     

基于多目标遗传算法和FLUS模型的西北农牧交错带土地利用优化配置

西北农牧交错带生态环境脆弱,区位特殊性和生态重要性使其在我国社会经济发展和生态环境保护方面具有重要战略意义。通过对该区域进行土地利用优化配置,使有限的土地资源支撑起生态环境保护和经济发展的重任是本文的出发点。多目标遗传算法和FLUS模型的应用可以从多方面（数量结构、空间布局、综合效益）完善土地利用优化配置,为土地利用优化配置提供更多的选择方案。本文选用多目标遗传算法和FLUS模型对该区域进行2025年的土地利用变化模拟,通过设置自然发展、生态保护优先、经济发展优先、生态-经济均衡4种情景,探讨了如何在兼顾生态环境保护与社会经济发展的情况下进行土地利用的优化配置。结果表明,基于生态-经济均衡情景下的优化方案,土地利用类型的数量结构和空间布局更为合理,其综合效益优于另外3种情景。该情景在合理限制经济发展速度的前提下,使生态建设获得稳定发展,其经济效益较生态保护优先情景下增长了8.96%,生态效益较经济发展优先情景下增长了0.77%,在生态保护与经济发展2种目标之间达到平衡,为西北农牧交错带的土地利用规划提供了决策辅助。     

Data Configurations and the Cokriging System: Simplification by Screen Effects

Large cokriging systems arise in many situations and are difficult to handle in practice. Simplifications such as simple kriging, strictly collocated and multicollocated cokriging are often used and models under which such simplifications are, in fact, equivalent to cokriging have recently received attention. In this paper, a two-dimensional second-order stationary random process with known mean is considered and the redundancy of certain components of the data at certain locations vis-à-vis the solution to the simple cokriging system is examined. Conditions for the simple cokriging weights of these components at these locations are set to zero. The conditions generalise the notion of the autokrigeability coefficient and can, in principle, be applied to any data configuration. In specific sampling situations such as the isotopic and certain heterotropic configurations, models under which simple kriging, strictly collocated, multicollocated and dislocated cokriging are equivalent to simple cokriging are readily identified and results already available in the literature are obtained. These are readily identified and the results are already available in the literature. The advantage of the approach presented here is that it can be applied to any data configuration for analysis of permissible simplifications in simple cokriging.     

Markov chain Monte Carlo methods for conditioning a permeability field to pressure data

Generating one realization of a random permeability field that is consistent with observed pressure data and a known variogram model is not a difficult problem. If, however, one wants to investigate the uncertainty of reservior behavior, one must generate a large number of realizations and ensure that the distribution of realizations properly reflects the uncertainty in reservoir properties. The most widely used method for conditioning permeability fields to production data has been the method of simulated annealing, in which practitioners attempt to minimize the difference between the ’ ’true and simulated production data, and “true” and simulated variograms. Unfortunately, the meaning of the resulting realization is not clear and the method can be extremely slow. In this paper, we present an alternative approach to generating realizations that are conditional to pressure data, focusing on the distribution of realizations and on the efficiency of the method. Under certain conditions that can be verified easily, the Markov chain Monte Carlo method is known to produce states whose frequencies of appearance correspond to a given probability distribution, so we use this method to generate the realizations. To make the method more efficient, we perturb the states in such a way that the variogram is satisfied automatically and the pressure data are approximately matched at every step. These perturbations make use of sensitivity coefficients calculated from the reservoir simulator.     

The GF algorithm for reservoir storage, yield and spillage distributions for non-seasonal and seasonal independent inflow processes

a well-known generating function formula for the equilibrium storage distribution in a finite Moran reservoir having IID inflows and unit release is extended to apply to a class of nondecreasing staircase-like release policies withm unit increments,m>1, and to seasonal inflows. The analysis is conducted in terms of an alternative to the Moran inflow-outflow sequencing scheme, with the release during a working interval controlled by the water level at the beginning of that interval.In addition to the storage, the equilibrium distributions of yield and spillage are obtained. Illustrative examples are provided.     

Predicting cumulative sediment depostition in large reservoirs

Sediment deposition and its accumulation in a large resorvoir depends on the inflow and reservoir storage content, respectively. Because of this fact it is possible to model the cumulative deposition of sediment as an additive process defined on a bivariate Markov chain. Using the bivariate Markov chain model the mean and variance of the cumulative deposition of John Martin Reservoir, Colorado, U.S.A. are estimated and compared with observed sedimentation data.     

Food security,remoteness and consolidation of supermarket distribution centres: Factors contributing to food pricing inequalities across Queensland,Australia

There is a clear association between food prices, affordability and issues of food security. Australian food supply chains have lengthened in recent years in response to consolidation policies of the dominant supermarkets, which have reduced the number of distribution centres in order to maximise economic efficiencies. This study presents a spatial analysis of a healthy food basket survey undertaken across Queensland, Australia in order to identify the primary determinants of food pricing. Ambiguity in the academic literature on this subject is largely due to limitations of the utilised methods. Our results indicate that food price variability is directly related to the type of store surveyed, and the distance of the surveyed store to the supermarket distribution centres in Brisbane, or urban centres on the east coast of Australia. Population size of towns and the level of social disadvantage observed in communities were indirect determinants of food prices. Therefore, in order to lessen the disadvantage already encountered by communities located in outer regional and remote areas who pay increasingly more for food than their urban counterparts, policy interventions need to move beyond subsiding food costs and consider the relationship between fuel prices and the lengthening of dominant food supply chains, in addition to the capacity of local supply chains.