The Internet accelerates the communication and understandings between people, which make information unprecedented important. Furthermore, it changes the way that people book rooms, which makes rooms-booking diversifi...
详细信息
The prediction of financial distress for financial institutions has been extensively researched for a long time. Latest studies have shown that such ensemble techniques have performed better than single AI technique i...
详细信息
In traditional study of mining data stream, each item in the data stream is of equal importance. However, in practice, each item has a different significance, which is known as utility. This paper combines frequent mi...
详细信息
In data stream mining, sliding window can record the latest and most useful patterns, but the best size can not be accurately determined. To aim at data with the characteristics of data flow in some simulation systems...
详细信息
To resolve the problem of short-term power load forecasting, we propose a self-adapting particle swarm optimization (PSO) algorithm to optimize the error back propagation (BP) neural network model. The proposed model ...
详细信息
Objective : This study is to investigate the personality characteristics of student volunteers, which would provide a reference to select and train qualified volunteers for the future. Methods : 233 student volunteers...
详细信息
Objective : This study is to investigate the personality characteristics of student volunteers, which would provide a reference to select and train qualified volunteers for the future. Methods : 233 student volunteers and 236 non-volunteers are selected for our study. Based on the data of 16PF personality exported from the database, statistical software SPSS15.0 is used to conduct data analysis. Result : Volunteers and non-volunteers have significant differences of personality: the 16 basic personality factors, the gregariousness, excitement, daring and independence scores are significantly different; in the other eight binary factors, emotional and serene in the alert type, introverted and extroverted type, timid and bold type factors have significantly different scores. Male and female volunteers have significant personality difference in some respects. Conclusion : College student volunteers have obvious personality traits of extroversion, optimism, cheerfulness, enthusiasm, self-confidence etc. In addition, male and female volunteers have gender differences in personality characteristics in some aspects.
The purpose of this paper is to probe into the rules of medicine compounding for stroke prevention treated by Xin'an physicians by data mining. The method is in two steps. First step is to build the database of th...
详细信息
This paper used Gauss-Chebyshev formula to construct a new class of gray prediction model- GCGM (1,1) to overcome the lack of existed gray model and made accurate forecasting of electricity consumption for power engin...
详细信息
This paper used Gauss-Chebyshev formula to construct a new class of gray prediction model- GCGM (1,1) to overcome the lack of existed gray model and made accurate forecasting of electricity consumption for power engineering. A case study using the power engineering data of China is presented to demonstrate the effectiveness of our approach.
In traditional study of mining data stream, each item in the data stream is of equal importance. However, in practice, each item has a different significance, which is known as utility. This paper combines frequent mi...
详细信息
In traditional study of mining data stream, each item in the data stream is of equal importance. However, in practice, each item has a different significance, which is known as utility. This paper combines frequent mining item sets with utility and proposes an efficient algorithm for utility frequent pattern mining (UFPM). It combines bitmap with tree structure that can store and update the pattern of data stream quickly and completely by scanning only once. The algorithm generated by lexicographic order, proposes a novel tree U-tree and makes convenience for pattern updating and user reading. With a pattern growth approach in mining, the algorithm can effectively avoid the problem of a mass candidacy generation by level-wise searching. The experiments results show that our algorithm which is in high efficiency and good scalability outperforms the existing analogous algorithm.
From the perspective of supporting decisionmaking, a statistical model is built in this paper in order to realize the tradeoff between the accuracy of OLAP queries and the efficiency of OLAP processes. Kernel density...
详细信息
暂无评论