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One of the primary aims of China's territory spatial planning is to control the urban sprawl of local municipals and prevent regional competition and the negative consequences on the environment—which emphasizes the top-down spatial regulation. Indeed, the traditional cellular automaton (CA) model still has limitations when applied to the whole administration area since it may ignore the differences among cities and towns. Thus, this paper proposed a CM-CA (clustering, multi-level logit regression, integrated with cellular automaton) framework to simulate urban growth boundaries for cities and towns simultaneously. The significant novelty of this framework is to integrate several urban growth modes for all cities and towns. We applied our approach to the city of Xi'an, China, and the results showed satisfactory simulation accuracy of a CM-CA model for multiple cities and towns, and the clusters' effects contributed 74% of the land change variance. Our study provides technical support for urban growth boundary delineation in China's spatial planning. [ABSTRACT FROM AUTHOR]

To explore companion movement laws of different age groups and transfer rules of panic emotion during evacuation at subway stations, evacuation groups of different ages were distinguished in this study through differences in movement rate. Moreover, a double-exit subway cellular automaton evacuation model considering companion behaviours was constructed. A case study of evacuation of dense crowds at the Hukou Subway in Wuhan City of China was simulated, and effects of personnel structure, companion behaviours, and panic emotion on evacuation efficiency were analysed. Results show that, (1) the overall crowd evacuation time present a linear growth trend with the increase of pedestrian density. (2) The evacuation time initially decreases and then increases with the increase of companion ratio. The shortest evacuation time is achieved when the companion cells account for 10 %. (3) People are more reasonable and the general evacuation efficiency is higher if they can control emotions better during evacuation. The obtained conclusions provide great references to analyse companion behaviours of different age groups during evacuation. [ABSTRACT FROM AUTHOR]

Land use and land cover change (LUCC) modeling is crucial to urban planning and policy making. A well-used and effective paradigm for LUCC is the ANN-CA model which employs an artificial neural network (ANN) to calculate a transition probability over each land cell from various driving factors, and then uses a cellular automaton (CA) to evolve all cells consecutively to update their land usage and coverage according to the estimated probability distribution. This paper focuses on the effect of delays or perturbations possibly taking place between land cells on the LUCC modeling. To this end, a new ANN-CA model is proposed which adopts an asynchronous communicating cellular automaton (ACCA), rather than the conventional synchronous CA. Especially, the ACCA allows every cell to communicate with its neighbors independently at random times via a specific protocol, which offers a natural way to include stochastic delays in exchanging the current land usages between cells. As a result, every change of a cell's land use in the ACCA may not affect its neighbors immediately, but is subject to delays that might play an important role in modeling the practical LUCC. Numerical analysis of the new model are carried out over three regions of Chongqing city, China with different scales: Yongchuan District, Sanjiao Town, and Huangguashan Village, and experimental results demonstrate that the proposed ANN-ACCA model can achieve a higher accuracy for LUCC simulation as compared to conventional ANN-CA models. [ABSTRACT FROM AUTHOR]

This paper is committed to design an urban road intersection simulation model to simulate traffic scenario and mirror the intricate traffic characteristics in the urban road intersection. In order to identify the underlying mechanism of traffic jams in the urban road intersections, traffic characteristics of urban road intersection is investigated from a global perspective and the influence degree of intersections which is affected by pedestrians and vehicles is explored by setting the probability of pedestrians and vehicles running red light in this paper. In order to achieve the above objectives, the mechanism of motor vehicle and pedestrian of urban road intersection is analyzed from the aspects of the dynamic characteristics, the static characteristic and the social features based on the previous study. And then, a cellular automaton model, which integrates the relation of vehicle speed, vehicle changing lanes, vehicle running red light, and pedestrian running red, is established on condition of local road network using MATLAB. After traffic situation is highly simulated by cellular automaton model of urban road intersection, it is found that complex traffic rules make vehicles detained in the intersection, which deteriorates the traffic conditions of intersection. Pedestrians and vehicles running red light will make the intersection get into disorder and vehicles running red light has a worse influences on the traffic situation than pedestrians do in the intersection. [ABSTRACT FROM AUTHOR]

Abstract: Due to the life cycle complexity of Schistosoma japonicum and the characteristics of schistosomias is immuno-epidemiology, it is very challenging to give a group of certain rules and thus describe the transmission dynamics of S. japonicum with modelling approaches. Most existing epidemiological models for schistosomias is based on differential equations only track average worm burden without taking into account the individual variations, thus bear limitations on individual infection status monitoring and interpretation. In this paper, an improved stochastic model based on cellular automaton (I-SjCA, briefly) has been introduced to describe the transmission dynamics of human schistosomiasis japonica in an endemic area in China. This model reflects the process of the pathogen invasion from exposure to worm development and worm death when the infection is cleared; it also incorporates seasonality of infection, and stochastic behaviour of each individual in the study field. We show that based on the data collected from the 706 study participants, the model-predicted prevalence and intensity of S. japonicum in the 2nd year of investigation is comparable with the observation. Furthermore, we illustrate the use of model for evaluating possible control strategies for schistosomiasis in context of simulated prevalence and individual infection probability. The simulation results suggest that chemotherapy should cover no less than 85% of the S. japonicum infected population to guarantee an effective drug control program, and the best time for annual chemotherapy with praziquantel is the beginning of spring in the endemic area. Our findings indicate that I-SjCA model based on the cellular automaton can effectively simulate the transmission process. It is anticipated that our cellular automaton transmission model can serve as a tool for understanding schistosomiasis transmission dynamics and thus be conductive to build an effective control program. [Copyright &y& Elsevier]