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In fuzzy time-series methods, mining fuzzy logical relation (FLR) from time-series is one of most critical processes to influence forecasting accuracy. However, in stock markets, investors usually make their investment decisions according to recent stock information such as market news, technical indicators or yesterday price. In this paper, we propose a new fuzzy time-series, which integrates linear...
The Internet is becoming a spreading platform for the public opinion. It's important to model the Internet public opinion activity as accurate as possible. Hidden Markov Model (HMM) is introduced to describe the activity of the Internet public opinion. The state of the Internet public opinion is represented as the hidden state of HMM, and its characteristic is considered as the visible states in HMM...
This paper presents a time series' representation by eigenvector sequence based on wavelet transform. This representation is applicable for recognizing astronaut's respiratory intensity. By wavelet analysis, the time series of respiratory intensity is separated into noise and de-noised curve. Noise filtered effectively, the de-noised curve is smooth enough for facile subsection. According to such...
This paper studied the representation of time series. The signal and the noise separated by wavelet analysis, the whole data sampling was divided into many continuous intervals, in which the signal was monotone. Each interval was fitted by n-degree polynomial and its eigenvector was made up of the coefficients of the polynomial, its width and signal noise ratio (SNR). The eigenvectors of continuous...
The purpose of gene mapping is to identify the causal genetic regions of a specific phenotype mainly a complex disease. Most complex diseases are believed to have multiple contributing loci often having subtle patterns which make them fairly difficult to find in large datasets. We present and discuss a new criterion called conditional mutual information for association mapping and compare it to the...
This paper proposes a granular ranking algorithm for mining market values, gives the framework of algorithm and the concrete algorithm steps. The core of new algorithm is the construction of granular ranking function rG (x), which guides instances in the testing dataset finish ranking. The ranked result has a strong readability. The new algorithm improves the computation efficiency further relative...
In this paper, a new signal denoising algorithm from wavelet transform modulus maxima (WTMM) is proposed. It essentially combines Mallat's multiresolution analysis(MRA) theory and Donoho's denoising approach. With WTMM, we can improve the signal reconstruction approach and then an automatic denoising algorithm is possible. This method is of explicit physical meaning and can be implemented conveniently...
OLAP (on-line analytical processing) queries tend to be complex and ad hoc, often requiring computationally expensive operations such as multi-table joins and aggregation. In the high dimensional data warehouse(DW), we full materialized the data cube impossibly. In this paper, we propose a novel aggregation algorithm, PDHEPA (parallel pre-grouping aggregation based on the dimension hierarchical encoding),...
Modern organizations are geographically distributed. Using the traditional centralized association rule mining to discover useful patterns in such distributed system is not always feasible because merging data sets from different sites into a centralized site incurs huge network communication and time costs. This paper presents an efficient distributed association rule mining (ED-ARM) algorithm to...
The common association rules mining methods in multiple databases were inefficient due either to larger amount of candidate itemsets for communication overhead or higher times of database scan. Based on discussing the relation between the concept of pruned concept lattice and the representation of frequent itemsets, the closed frequent itemsets of pruned concept lattice was defined. UMPCL, an approximately...
With MPI and C/C++, a parallel algorithm of molecular dynamics based on octal-tree domain decomposition method was implemented for micro canonical system (NVE), and run the code on a small cluster. The code speed-up was examined for a number of particles ranging from N = 192 to 10800 and for number of processors from P = 2 up to 8. As a result, the computing performance has been improved obviously,...
Estimating similarity over data streams has many applications in the data streams environment, such as intrusion detection in the network, data analysis in the sensor net, cluster, k-nearest neighbor queries and so on. However, there has only a few research related to similarity evaluation under data stream contexts. The main reason is because of the native feature of data streams, namely, large,...
To improve the intelligibility and efficiency of the land evaluation knowledge, a land evaluation method integrating simplified fuzzy classification association rules with fuzzy decision is proposed in this paper. Moreover, to reduce the complexity of the land evaluation models, an algorithm to eliminate redundant rules for obtaining the simplified fuzzy classification association rules is presented...
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