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A spatial multi-objective land use optimization model defined by the acronym 'NSGA-II-MOLU' or the 'non-dominated sorting genetic algorithm-II for multi-objective optimization of land use' is proposed for searching for optimal land use scenarios which embrace multiple objectives and constraints extracted from the requirements of users, as well as providing(More)
I. THE HIBENCH SUITE MapReduce and its popular open source implementation, Hadoop, are moving toward ubiquitous for Big Data storage and processing. Therefore, it is essential to quantitatively evaluate and characterize the Hadoop deployment through extensive benchmarking. In this paper, we present HiBench [1], a representative and comprehensive benchmark(More)
This paper presents an improved cellular automata (CA) model optimized using an adaptive genetic algorithm (AGA) to simulate the spatio-temporal process of urban growth. The AGA technique can be used to optimize the transition rules of the CA model defined through conventional methods such as logistic regression approach, resulting in higher simulation(More)
This paper presents a method to optimise the calibration of parameters and land use transition rules of a cellular automata (CA) urban growth model using a self-adaptive genetic algorithm (SAGA). Optimal calibration is achieved through an algorithm that minimises the difference between the simulated and observed urban growth. The model was applied to(More)
We are on the verge of the " industrial revolution of Big Data, " which represents the next frontier for innovation, competition, and productivity. [1]. Big data is rich with promise, but equally rife with challenges—it extends beyond traditional structured (or relational) data, including unstructured data of all types; it is not only large in size, but(More)
A critical issue in urban cellular automata (CA) modeling concerns the identification of transition rules that generate realistic urban land use patterns. Recent studies have demonstrated that linear methods cannot sufficiently delineate the extraordinary complex boundaries between urban and non-urban areas and as most urban CA models simulate transitions(More)
To cite this article: Yan Liu (2012): Modelling sustainable urban growth in a rapidly urbanising region using a fuzzy-constrained cellular automata approach, This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or(More)
This is the first part of a two-paper series elaborating the development of a cellular automaton model of urban development using GIS and fuzzy set approaches. Under the paradigm of fuzzy set theory, this paper develops a cellular automaton model of urban development based on an understanding of the logistic trend of urban development processes. The model(More)