Big Data, Factor Agglomeration of Urban Economics and Spatial Chaos

The sensitiveness of big data to the space and time brings many difficulties in the process of the big data analysis, modeling and predicting, especially in the factor agglomeration of labor, capital and technology. Hence, how to study the complex characteristics of these factors in urban economics development remains important and significant. A coupled discrete system combining the technology, labor, capital and pollution terms are present by the finite difference method. The stable and chaotic theories and simulation results of the effect of the technology term on the pollution term in this coupled system are illustrated by the spatial chaotic theory.