Decreased routing path based on a dynamic prediction algorithm for mobile sink in WSN

2007 ◽  
Author(s):  
Weiwei Jiao ◽  
Dongliang Xie ◽  
Wenbin Yu ◽  
Jian Ma ◽  
Shiduan Cheng
Keyword(s):  
Mobile Sink ◽  
Prediction Algorithm ◽  
Dynamic Prediction

scholarly journals Dynamic Prediction of Financial Distress Based on Kalman Filtering

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Qian Zhuang ◽  
Lianghua Chen
Keyword(s):  
Kalman Filtering ◽  
Financial Distress ◽  
Process Model ◽  
Manufacturing Industry ◽  
Prediction Models ◽  
Prediction Algorithm ◽  
Dynamic Prediction ◽  
Discriminant Model ◽  
Financial Distress Prediction ◽  
Distress Prediction

The widely used discriminant models currently for financial distress prediction have deficiencies in dynamics. Based on the dynamic nature of corporate financial distress, dynamic prediction models consisting of a process model and a discriminant model, which are used to describe the dynamic process and discriminant rules of financial distress, respectively, is established. The operation of the dynamic prediction is achieved by Kalman filtering algorithm. And a generaln-step-ahead prediction algorithm based on Kalman filtering is deduced in order for prospective prediction. An empirical study for China’s manufacturing industry has been conducted and the results have proved the accuracy and advance of predicting financial distress in such case.

scholarly journals A Wavelet Analysis-Based Dynamic Prediction Algorithm to Network Traffic

2016 ◽  
Vol 7 ◽  
pp. 09025
Author(s):  
Fan-Bo Meng ◽  
Hong-Hao Zhao ◽  
Si-Hang Zhao ◽  
Si-Wen Zhao ◽  
Zhong-Qiu Lin
Keyword(s):  
Wavelet Analysis ◽  
Network Traffic ◽  
Prediction Algorithm ◽  
Dynamic Prediction

scholarly journals International trade and finance exploration using network model of computer trade platform

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260883
Author(s):  
Yi Zhang ◽  
Yi Yuan
Keyword(s):  
Big Data ◽  
International Trade ◽  
Foreign Trade ◽  
Network Model ◽  
Forecast Error ◽  
Rapid Development ◽  
Practical Significance ◽  
Prediction Algorithm ◽  
Dynamic Prediction ◽  
Prediction Mechanism

International trade becomes increasingly frequent with the deepening of economic globalization. In order to ensure the stable and rapid development of international trade and finance, it is particularly crucial to predict the sales trend of foreign trade goods in advance through the network model of computer trade platform. To optimize the accuracy of sales forecasts for foreign trade goods, under the background of "Internet plus foreign trade", the controllable relevance big data mining of foreign trade goods sales, personalized prediction mechanism, intelligent prediction algorithm, improved distributed quantitative and centralized qualitative calculation are taken as the premise to design dynamic prediction model on export sales based on controllable relevance big data of cross border e-commerce (DPMES). Moreover, after the related experiments and comparative discussions, the forecast error ratios from the first quarter to the fourth quarter are 2.3%, 2.1%, 2.4% and 2.4% respectively, which are also within the acceptable range. The experimental results show that the design combines the advantages of openness and extensibility of Internet plus with dynamic prediction of big data, and achieves the wisdom, quantitative and qualitative prediction of the volume of goods sold under the background of "Internet plus foreign trade", which is controlled by the relevant data of foreign trade. The overall performance of this design is stronger than the previous models, has better dynamic evolution and high practical significance, and is of great significance in the development of international trade and finance.

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