The research into an improved algorithm of telecommunication inter-transactional association rules based on time series of all confidence

2009 ◽  
Author(s):  
Wenchuan Yang ◽  
Chao Dong ◽  
Jie Cheng ◽  
Fang Fang
Keyword(s):  
Time Series ◽  
Association Rules ◽  
Improved Algorithm

Improved Apriori Algorithm in the Power System Fault

2014 ◽  
Vol 556-562 ◽  
pp. 1510-1514
Author(s):  
Li Qiang Lin ◽  
Hong Wen Yan
Keyword(s):  
Power System ◽  
Association Rules ◽  
Fault Analysis ◽  
The Other ◽  
Apriori Algorithm ◽  
Extreme Climate ◽  
Time Space ◽  
Low Efficiency ◽  
Candidate Item ◽  
Improved Algorithm

For the low efficiency in generating candidate item sets of apriori algorithm, this paper presents a method based on property division to improve generating candidate item sets. Comparing the improved apriori algorithm with the other algorithm and the improved algorithm is applied to the power system accident cases in extreme climate. The experiment results show that the improved algorithm significantly improves the time efficiency of generating candidate item sets. And it can find the association rules among time, space, disasters and fault facilities in the power system accident cases in extreme climate. That is very useful in power system fault analysis.

A Novel and Improved Apriori Algorithm

2014 ◽  
Vol 721 ◽  
pp. 543-546 ◽  
Author(s):  
Dong Juan Gu ◽  
Lei Xia
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Inner Product ◽  
Apriori Algorithm ◽  
Product Operation ◽  
Classical Algorithm ◽  
Transaction Database ◽  
The Given ◽  
To Receive ◽  
Improved Algorithm

Apriori algorithm is the classical algorithm in data mining association rules. Because the Apriori algorithm needs scan database for many times, it runs too slowly. In order to improve the running efficiency, this paper improves the Apriori algorithm based on the Apriori analysis. The improved idea is that it transforms the transaction database into corresponding 0-1 matrix. Whose each vector and subsequent vector does inner product operation to receive support. And comparing with the given minsupport, the rows and columns will be deleted if vector are less than the minsupport, so as to reduce the size of the rating matrix, improve the running speeding. Because the improved algorithm only needs to scan the database once when running, therefore the running speeding is more quickly. The experiment also shows that this improved algorithm is efficient and feasible.

Trend-Based Time Series Prediction Algorithm

2010 ◽  
Vol 108-111 ◽  
pp. 1164-1169
Author(s):  
Xin Qi ◽  
Hong Liang ◽  
Zhen Li
Keyword(s):  
Time Series ◽  
Monitoring System ◽  
Time Series Prediction ◽  
Prediction Algorithm ◽  
Short Term ◽  
Grid Monitoring ◽  
Status Information ◽  
Term Performance ◽  
Improved Algorithm

According to the resources performance and status information provided by grid monitoring system, this paper adopts a trend-based time series prediction algorithm to predict short-term performance of the resources. Experiments show that the improved mixed trend-based prediction algorithm tracks the trend of data changes by giving more weight, simultaneously takes the different situations of data increases and decreases into account, so the improved algorithm is superior to the pre-improved and it improves the accuracy of the prediction effectively.

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