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It is very important to understand urban mobility patterns because most trips are concentrated in urban areas. In the paper, a new model is proposed to model collective human mobility in urban areas. The model can be applied to predict…

Physics and Society · Physics 2014-10-28 Xiao Liang , Jichang Zhao , Li Dong , Ke Xu

Over the last decades, in disciplines as diverse as economics, geography, and complex systems, a perspective has arisen proposing that many properties of cities are quantitatively predictable due to agglomeration or scaling effects. Using…

Physics and Society · Physics 2015-10-06 Luis M. A. Bettencourt , Jose Lobo

We introduce a model in which city populations grow at rates proportional to the area of their "sphere of influence", where the influence of a city depends on its population (to power \alpha) and distance from city (to power -\beta) and…

Physics and Society · Physics 2012-09-25 David Aldous , Bowen Huang

We consider the scaling laws, second-order statistics and entropy of the consumed energy of metropolis cities which are hybrid complex systems comprising social networks, engineering systems, agricultural output, economic activity and…

Physics and Society · Physics 2017-12-18 Syed Amaar Ahmad

A practical statistical analysis on the regional populations and GDPs of China is conducted. The result shows that the distribution of the populations and that of the GDPs obeys the shifted power law, respectively. To understand these…

Physics and Society · Physics 2018-02-14 Jie Huo , Xu-Ming Wang , Rui Hao , Peng Wang

In this paper, we introduce a new four-parameter generalized version of the Gompertz model which is called Beta-Gompertz (BG) distribution. It includes some well-known lifetime distributions such as beta-exponential and generalized Gompertz…

Statistics Theory · Mathematics 2014-07-04 Ali Akbar Jafari , Saeid Tahmasebi , Morad Alizadeh

Urban road networks have distinct geometric properties that are partially determined by their (quasi-) two-dimensional structure. In this work, we study these properties for 20 of the largest German cities. We find that the small-scale…

Data Analysis, Statistics and Probability · Physics 2015-05-27 Sonic H. Y. Chan , Reik V. Donner , Stefan Lämmer

We consider a version of D. Price's model for the growth of a bibliographic network, where in each iteration a constant number of citations is randomly allocated according to a weighted combination of accidental (uniformly distributed) and…

Physics and Society · Physics 2022-08-31 Grzegorz Siudem , Przemysław Nowak , Marek Gagolewski

Random partition distribution is a crucial tool for model-based clustering. This study advances the field of random partition in the context of functional spatial data, focusing on the challenges posed by hourly population data across…

Methodology · Statistics 2025-06-05 Tomoya Wakayama , Shonosuke Sugasawa , Genya Kobayashi

We propose a quantitative method to classify cities according to their street pattern. We use the conditional probability distribution of shape factor of blocks with a given area, and define what could constitute the `fingerprint' of a…

Physics and Society · Physics 2014-10-09 Rémi Louf , Marc Barthelemy

Map generalization is a process of producing maps at different levels of detail by retaining essential properties of the underlying geographic space. In this paper, we explore how the map generalization process can be guided by the…

Data Analysis, Statistics and Probability · Physics 2013-10-22 Bin Jiang , Xintao Liu , Tao Jia

Beta Rank Function (BRF) is a two-sided distribution characterized by a smooth peak and double powerlaw decay, widely used to model empirical data exhibiting deviations from pure power laws. In this paper, we introduce a novel two-step…

Physics and Society · Physics 2026-01-28 Oscar Fontanelli , Wentian Li

The interaction of all mobile species with their environment hinges on their movement patterns: the places they visit and how frequently they go there. In human society, where the prevalent form of cohabitation is in cities, the highly…

Physics and Society · Physics 2020-02-17 Markus Schläpfer , Michael Szell , Hadrien Salat , Carlo Ratti , Geoffrey B. West

A longstanding puzzle in urban science is whether there's an intrinsic match between human populations and the mass of their built environments. Previous findings have revealed various urban properties scaling nonlinearly with population,…

Physics and Society · Physics 2025-08-11 Kangning Huang , Mingzhen Lu

A new technique of global optimization and its applications in particular to neural networks are presented. The algorithm is also compared to other global optimization algorithms such as Gradient descent (GD), Monte Carlo (MC), Genetic…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-18 Homayoun Valafar , Okan K. Ersoy , Faramarz Valafar

Many studies in Economics and other disciplines have been reporting distributions following power-law behavior (i.e distributions of incomes (Pareto's law), city sizes (Zipf's law), frequencies of words in long sequences of text etc.)[1, 6,…

Mathematical Physics · Physics 2008-12-10 Francesco Vallone

We introduce a predictive algorithm for the smart growth of cities with populations upward of 100,000, allowing for extensive simulations of growth plans and their effects upon an urban populous. A smart growth metric is calculated to…

Physics and Society · Physics 2017-12-01 James Flamino , Alexander Norman , Madison Wyatt

Urban sprawl reshapes cities, yet its quantitative laws remain elusive. Analyzing built-up expansion in 19 cities (1985-2015) with tools from surface growth physics in radial geometry, we reveal anisotropic, branch-like growth and a…

Physics and Society · Physics 2025-11-04 Ulysse Marquis , Oriol Artime , Riccardo Gallotti , Marc Barthelemy

The beta distribution is the best-known distribution for modelling doubly-bounded data, \eg percentage data or probabilities. A new generalization of the beta distribution is proposed, which uses a cubic transformation of the beta random…

Methodology · Statistics 2016-12-19 Rose Baker

Data-driven Distributionally Robust Optimization (DD-DRO) via optimal transport has been shown to encompass a wide range of popular machine learning algorithms. The distributional uncertainty size is often shown to correspond to the…

Machine Learning · Statistics 2021-05-12 Jose Blanchet , Yang Kang , Fan Zhang , Fei He , Zhangyi Hu
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