This article uses a logarithmic growth model to analyze the correlation between the national economy and real estate. It reveals the Granger causality between the national economy and the real estate economy. The results show a long-term equilibrium relationship and a two-way Granger causality between real estate prices and economic growth. Excessive growth in real estate prices will create bubbles and will also drive economic growth backward.
Economic growth in the information age is no longer a stage driven by unipolarity. It has entered a multi-polar driving stage characterized by integration, fusion, and integrated development on a larger scale between regions, and the trend of group competition with urban agglomerations as carriers has become increasingly obvious. This paper improves the neural network algorithm based on the needs of industrial economic integration in the digital age, and proposes an industry convergence analysis model based on the improved neural network algorithm. Moreover, this article combines industry models to analyze actual needs and constructs an industry convergence analysis model based on improved neural networks, and analyzes the integration of different industries. In addition, this article conducts experiments through multiple sets of data, and combines the neural network model of this article to conduct research. Through experimental research, we know that the model constructed in this paper can play an important role in the analysis of industry convergence.
Abstract. The forecast of oil demand in large oil depot is the main basis for the allocation of oil and distribution. The accurate and efficient real-time forecast of oil demand is an important guarantee for the effective management and rational use of oil. In this paper, the amount of oil in and out of large oil depots is abstracted into time series model, and the main factors influencing the time series are extracted by time series decomposition method. The calculation process and the changing rules of these factors are studied, and the forecasting model of oil demand of large oil depot is constructed. The example shows that the time series decomposition method can realize the effective forecast of large oil depot demand.
Economic growth in the information age is no longer a stage driven by unipolarity. It has entered a multi-polar driving stage characterized by integration, fusion, and integrated development on a larger scale between regions, and the trend of group competition with urban agglomerations as carriers has become increasingly obvious. This paper improves the neural network algorithm based on the needs of industrial economic integration in the digital age, and proposes an industry convergence analysis model based on the improved neural network algorithm. Moreover, this article combines industry models to analyze actual needs and constructs an industry convergence analysis model based on improved neural networks, and analyzes the integration of different industries. In addition, this article conducts experiments through multiple sets of data, and combines the neural network model of this article to conduct research. Through experimental research, we know that the model constructed in this paper can play an important role in the analysis of industry convergence.
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