An analytical process of the spatio-temporal evolution of urban systems based on allometric and fractal ideas

This paper presents a computer-based analytical framework for the spatio-temporal evolution of urban systems using the ideas from the allometric growth associated with fractals. Both cities as systems and systems of cities follow the law of allometric growth, and the scaling factors of the allometric relations can compose the matrix equations as eigenfunctions. The fractal dimension arrays are just the eigenvectors of the scaling factor matrices while the numbers of variables are the greatest eigenvalues. The solutions of matrix equations can be employed to analyse city systems and evaluate relative levels of urban development. The method is applied to Hangzhou urban system of China. The results reveal clearly an urbanization process characterized as population concentration and an industrialization process characterized as industrial diffusion. The computation results are consistent with the reality, which indicate that the method is available for analyzing the spatio-temporal evolution of complex systems such as cities.     

Fractal dimension evolution and spatial replacement dynamics of urban growth

This paper presents a new perspective of looking at the relation between fractals and chaos by means of cities. Especially, a principle of space filling and spatial replacement is proposed to interpret the fractal dimension of urban form. The fractal dimension evolution of urban growth can be empirically modeled with Boltzmann’s equation. For the normalized data, Boltzmann’s equation is just equivalent to the logistic function. The logistic equation can be transformed into the well-known 1-dimensional logistic map, which is based on a 2-dimensional map suggesting spatial replacement dynamics of city development. The 2-dimensional recurrence relations can be employed to generate the nonlinear dynamical behaviors such as bifurcation and chaos. A discovery is thus made in this article that, for the fractal dimension growth following the logistic curve, the normalized dimension value is the ratio of space filling. If the rate of spatial replacement (urban growth) is too high, the periodic oscillations and chaos will arise. The spatial replacement dynamics can be extended to general replacement dynamics, and bifurcation and chaos mirror a process of complex replacement.     

Fractal-based exponential distribution of urban density and self-affine fractal forms of cities

Urban population density always follows the exponential distribution and can be described with Clark’s model. Because of this, the spatial distribution of urban population used to be regarded as non-fractal pattern. However, Clark’s model differs from the exponential function in mathematics because that urban population is distributed on the fractal support of landform and land-use form. By using mathematical transform and empirical evidence, we argue that there are self-affine scaling relations and local power laws behind the exponential distribution of urban density. The scale parameter of Clark’s model indicating the characteristic radius of cities is not a real constant, but depends on the urban field we defined. So the exponential model suggests local fractal structure with two kinds of fractal parameters. The parameters can be used to characterize urban space filling, spatial correlation, self-affine properties, and self-organized evolution. The case study of the city of Hangzhou, China, is employed to verify the theoretical inference. Based on the empirical analysis, a three-ring model of cities is presented and a city is conceptually divided into three layers from core to periphery. The scaling region and non-scaling region appear alternately in the city. This model may be helpful for future urban studies and city planning.     

The distance-decay function of geographical gravity model: Power law or exponential law?

The distance-decay function of the geographical gravity model is originally an inverse power law, which suggests a scaling process in spatial interaction. However, the distance exponent of the model cannot be reasonably explained with the ideas from Euclidean geometry. This results in a dimension dilemma in geographical analysis. Consequently, a negative exponential function was used to replace the inverse power function to serve for a distance-decay function. But a new puzzle arose that the exponential-based gravity model goes against the first law of geography. This paper is devoted for solving these kinds of problems by mathematical reasoning and empirical analysis. New findings are as follows. First, the distance exponent of the gravity model is demonstrated to be a fractal dimension using the geometric measure relation. Second, the similarities and differences between the gravity models and spatial interaction models are revealed using allometric relations. Third, a four-parameter gravity model possesses a symmetrical expression, and we need dual gravity models to describe spatial flows. The observational data of China's cities and regions (29 elements indicative of 841 data points) in 2010 are employed to verify the theoretical inferences. A conclusion can be reached that the geographical gravity model based on power-law decay is more suitable for analyzing large, complex, and scale-free regional and urban systems. This study lends further support to the suggestion that the underlying rationale of fractal structure is entropy maximization. Moreover, it suggests that many dimensional dilemmas of spatial modeling can be solved using the concepts from fractal geometry.     

A note on estimates for the growth order of sequences of multiple rectangular Fourier sums

We develop an optimal growth model of an open economy that uses both an old (“dirty” or “polluting”) technology and a new (“clean”) technology simultaneously. A planner of the economy expects the occurrence of a random shock that increases sharply abatement costs in the dirty sector. Assuming that the probability of an exogenous environmental shock is distributed according to the exponential law, we use Pontryagin’s maximum principle to find the optimal investment and consumption policies for the economy.     

CGMY模型下 的欧式外汇期权定价

修正传统有效市场假说,重新假设外汇汇率存在扩散和跳跃,并结合CGMY模型,采用傅里叶变换方法,推导出了CGMY模型下欧式外汇期权价格满足的分数阶偏微分方程(FPDE).尽管因分数阶偏导数引发的“全局性”很难处理,仍然推导出CGMY模型下欧式外汇期权的定价公式及其满足的平价公式.同时,引入一个新的缩放参数m来控制指数函数的增长率以克服被积函数衰减引起的计算困难,使其与Lévy密度函数的衰减在速度上达到一个平衡.最后,从数学与金融意义上分析了关键参数变化对欧式外汇期权价格的影响.     

Modelling population growth vialaguerre-type exponentials

We use the Laguerre-type exponentials, i.e., eigenfunctions of the Laguerre-type derivatives, in order to construct new models for population growth. Relevant modifications of the classical exponential, logistic, and Volterra-Lotka models are investigated.     

Natural selection: A concept in need of some evolution?

In some respects natural selection is a quite simple theory, arrived at through the logical integration of three propositions (the presence of variation within natural populations, an absolutely limited resources base, and procreation capacities exceeding mere replacement numbers) whose individual truths can hardly be denied. Its relation to the larger subject of evolution, however, remains problematic. It is suggested here thata scaling‐down of the meaning of natural selection to “the elimination of the unfit,” as originally intended by Alfred Russel Wallace (1823–1913), might ultimately prove a more effective means of relating it to larger‐scale, longer‐term, evolutionary processes. © 2011 Wiley Periodicals, Inc. Complexity, 2011     

跳汰机的性能及统计模型

在煤用重选设备评定的国际标准（ＩＳＯ９２３）和以之为蓝本的国家标准（ＧＢ／Ｔ１５７１５）中的第一项评定指标“可能偏差”及和其有关的“不完善度”的确定是由以下步骤决定：１．由仅仅一次浮沉试验取得一组数据（一个观察值）并由此计算两段分离所得产品的分配率;２．用手工凭想象中的“Ｓ型曲线”把分配率中的两组６ 至８ 个点联起来得到两条“分配曲线”;３．由这两条粗糙的曲线“量出”各自的２５％ 和７５％ 分位点,以此得到能反映重选设备分离能力好坏的两个指标：“可能偏差”Ｅ和“不完善度”Ｉ,很难想象,这样由一个观察值得到的指标并通过没有模型的手工绘图而得到的结果会有任何实际意义,本文建议利用尽可能多的观察值来拟合ｌｏｇｉｓｔｉｃ回归模型,并依此得到分配曲线和计算出参数Ｅ和Ｉ,本文还利用一组实际数据来说明我们方法的合理性     

SBFEM elements for thin-walled composite beams with arbitrary layup

The scaled boundary finite element method (SBFEM) is a semi-analytical method in which only the boundary is discretized. The results on the boundary are scaled into the domain with respect to a scaling center which must be “visible” from the whole boundary. For beam-like problems the scaling center can be selected at infinity and only the cross-section is discretized. Two new elements for thin-walled beams have been developed on the basis of the first order shear deformation theory. The beam sections are considered to be multilayered laminate plates with arbitrary layup. The arbitrary cross-section is discretized with beam elements of Timoshenko type. Using the virtual work principle gives the SBFEM equation, which is a system of differential equations of a gyroscopic type. The solution is calculated using the matrix exponential function. The elements have been tested and compared with a finite element model and they give good results. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Correspondence and canonical analysis of relational data

Correspondence analysis, a data analytic technique used to study two‐way cross‐classifications, is applied to social relational data. Such data are frequently termed “sociometric” or “network” data. The method allows one to model forms of relational data and types of empirical relationships not easily analyzed using either standard social network methods or common scaling or clustering techniques. In particular, correspondence analysis allows one to model:

—two‐mode networks (rows and columns of a sociomatrix refer to different objects)

—valued relations (e.g. counts, ratings, or frequencies).

In general, the technique provides scale values for row and column units, visual presentation of relationships among rows and columns, and criteria for assessing “dimensionality” or graphical complexity of the data and goodness‐of‐fit to particular models. Correspondence analysis has recently been the subject of research by Goodman, Haberman, and Gilula, who have termed their approach to the problem “canonical analysis” to reflect its similarity to canonical correlation analysis of continuous multivariate data. This generalization links the technique to more standard categorical data analysis models, and provides a much‐needed statistical justificatioa

We review both correspondence and canonical analysis, and present these ideas by analyzing relational data on the 1980 monetary donations from corporations to nonprofit organizations in the Minneapolis St. Paul metropolitan area. We also show how these techniques are related to dyadic independence models, first introduced by Holland, Leinhardt, Fienberg, and Wasserman in the early 1980's. The highlight of this paper is the relationship between correspondence and canonical analysis, and these dyadic independence models, which are designed specifically for relational data. The paper concludes with a discussion of this relationship, and some data analyses that illustrate the fart that correspondence analysis models can be used as approximate dyadic independence models.     

Logistic biplot for nominal data

Classical biplot methods allow for the simultaneous representation of individuals (rows) and variables (columns) of a data matrix. For binary data, logistic biplots have been recently developed. When data are nominal, both classical and binary logistic biplots are not adequate and techniques such as multiple correspondence analysis (MCA), latent trait analysis (LTA) or item response theory (IRT) for nominal items should be used instead. In this paper we extend the binary logistic biplot to nominal data. The resulting method is termed “nominal logistic biplot”(NLB), although the variables are represented as convex prediction regions rather than vectors. Using the methods from computational geometry, the set of prediction regions is converted to a set of points in such a way that the prediction for each individual is established by its closest “category point”. Then interpretation is based on distances rather than on projections. We study the geometry of such a representation and construct computational algorithms for the estimation of parameters and the calculation of prediction regions. Nominal logistic biplots extend both MCA and LTA in the sense that they give a graphical representation for LTA similar to the one obtained in MCA.     

Designing a contact process: the piecewise-homogeneous process on a finite set with applications

We consider how to choose the reproduction rates in a one-dimensional contact process on a finite set to maximize the growth rate of the extinction time with the population size. The constraints are an upper bound on the average reproduction rate, and that the rate profile must be piecewise constant. We show that the optimum growth rate is achieved by a rate profile with at most two rates, and we characterize the solution in terms of a “spatial correlation length” of the supercritical process. We examine the analogous problem for the simpler biased voter model, for which we completely characterize the optimum profile. The contact process proofs make use of a planar-graph duality in the graphical representation, due to Durrett and Schonmann.     

POPULATION‐LEVEL ANALYSIS AND VALIDATION OF AN INDIVIDUAL‐BASED CUTTHROAT TROUT MODEL

ABSTRACT. An individual‐based model of stream trout is analyzed by testing its ability to reproduce patterns of population‐level behavior observed in real trout: (1) “self‐thinning,” a negative power relation between weight and abundance; (2) a “critical period” of density‐dependent mortality in young‐of‐the‐year; (3) high and age‐specific inter‐annual variability in abundance; (4) density dependence in growth; and (5) fewer large trout when pool habitat is eliminated. The trout model successfully reproduced these patterns and was useful for evaluating their theoretical basis. The model analyses produced new explanations for some field observations and indicated that some patterns are less general than field studies indicate. The model did not reproduce field‐observed patterns of population variability by age class, discrepancies potentially explained by site differences, predation mortality being more stochastic than the model assumes, or uncertainty in the field study's age estimates.     

Local computation in linear logic

This work deals with the exponential fragment of Girard's linear logic ([3]) without the contraction rule, a logical system which has a natural relation with the direct logic ([10], [7]). A new sequent calculus for this logic is presented in order to remove the weakening rule and recover its behavior via a special treatment of the propositional constants, so that the process of cut-elimination can be performed using only “local” reductions. Hence a typed calculus, which admits only local rewriting rules, can be introduced in a natural manner. Its main properties — normalizability and confluence — has been investigated; moreover this calculus has been proved to satisfy a Curry-Howard isomorphism ([6]) with respect to the logical system in question. MSC: 03B40, 03F05.     

The Bangladesh grain model

Determining the “optimal” number, size, location and design of grain storage facilities in a developing country is a complex problem with significant health, social, political, demographic and financial implications. Formulating and “solving” such a problem requires the consideration not only of average measures of demand (e.g. minimum per capita requirements), supply and costs, but of population movements, rationing systems, developments in domestic production due to new methods and fertilizers, severe limitations in foreign currency, the infra-structure of the transportation system, improvements in vermin control and many other factors which are most often of but minor importance in corresponding logistic studies in more developed countries. Furthermore, in comparison to more developed countries, there is a dearth of reasonably detailed and accurate historical data to say nothing of relevant prognoses.The following case study describes how such a nationwide logistics problem was tackled in Bangladesh. Although it leads up to a discussion of a solution procedure based upon the solution of rather large-scale mixed integer programming problems, the article is primarily intended for a target audience of OR practioners, economic planners and decision makers involved in operational planning for developing countries.     

Some predictability in one-dimensional chaotic dynamical systems arising in population models

Mathematical framework is given to “resolved chaos” studied numerically by Vandermeer in population biology, which means some kind of predictability in the chaotic dynamical systems. A general theory about one-dimensional unimodal maps is constructed. A quantity called “sojourning time,” which is the duration of staying in an interval by iteration of a map, is considered. Predictability is formulated as the size of error by fluctuation from the deterministic system. Topological entropy is used as the degree of chaos and a relation between topological entropy and sojourning time is obtained. Also, some conditions for the coexistence of chaotic behavior and predictability of sojourning time are given generally. In conclusion, many of the unimodal maps with high degree of chaos are predictable on the sojourning time.     

Evolutionary games with facilitators: When does selection favor cooperation?

We study the combined influence of selection and random fluctuations on the evolutionary dynamics of two-strategy (“cooperation” and “defection”) games in populations comprising cooperation facilitators. The latter are individuals that support cooperation by enhancing the reproductive potential of cooperators relative to the fitness of defectors. By computing the fixation probability of a single cooperator in finite and well-mixed populations that include a fixed number of facilitators, and by using mean field analysis, we determine when selection promotes cooperation in the important classes of prisoner’s dilemma, snowdrift and stag-hunt games. In particular, we identify the circumstances under which selection favors the replacement and invasion of defection by cooperation. Our findings, corroborated by stochastic simulations, show that the spread of cooperation can be promoted through various scenarios when the density of facilitators exceeds a critical value whose dependence on the population size and selection strength is analyzed. We also determine under which conditions cooperation is more likely to replace defection than vice versa.     

Buzzwords on their way to a tipping‐point: A view from the blogosphere

“Buzzwords” are new words (i.e., neologisms) that enter the language and acquire great popularity as “fashion words.” To date, the dynamic aspect of buzzwords has not been the subject of a rigorous scientific analysis. In this study, we analyzed the appearance of buzzwords in the blogosphere and compared their dynamics to the one of nonpopular neologisms and well‐established words. It was found that the growth rate of buzzwords is exponential and higher than that of the blogosphere. Moreover, we have identified general early warning signals for an approaching tipping point in the dynamics of buzzwords indicating that as fashion words they are on their way to a tipping‐point of decline. The article presents these findings and others and concludes by presenting a model for studying the dynamics of new words entering the language. © 2010 Wiley Periodicals, Inc. Complexity 16: 58‐68, 2011