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In Big Data applications, massive datasets with huge numbers of observations are frequently encountered. To deal with such massive datasets, a divide-and-conquer scheme (e.g., MapReduce) is often used for the analysis of Big Data. With such a strategy, a large dataset (e.g., a centralized real database or a virtual database with distributed data sources) is first divided into smaller manageable segments;...
For improving the forecasting accuracy of bank cash flow, a combined model based on back propagation (BP) neural network and grey prediction method is put forward based on the merits and demerits of both BP neural network and grey model prediction method. The proposed method has the advantage of two methods and makes up the deficiencies of single model as well. It can efficiently reduce the influence...
Minimum hop routing is an energy-efficient routing protocol with minimized energy consumption, but the reliability of data transmission is not enough. The routes tend to have a minimum hop count but contain weak links, which cause large number of data retransmissions. In this paper, a transmission power selection mechanism is proposed, where the power to transmit an overhead packet and a data packet...
Data-intensive computing becomes a buzz word nowadays, where constant data for current operational processing and historical data for massive analysis are often separated into two systems. How to keep the historical data for analysis (often in a materialized view manner) consistent with their data sources (often in the operational databases) is the main problem to be solved imperatively. In this paper,...
In order to better grasp the development trend and study the development path of service industry, this paper built ARIMA forecasting mode based on related statistical data from 1978 to 2008 to predict the service industry development of Sichuan Province, and analyze the forecast results.
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