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» A new evolutionary method for time series forecasting
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WINE
2005
Springer
268views Economy» more  WINE 2005»
14 years 1 months ago
Mining Stock Market Tendency Using GA-Based Support Vector Machines
In this study, a hybrid intelligent data mining methodology, genetic algorithm based support vector machine (GASVM) model, is proposed to explore stock market tendency. In this hyb...
Lean Yu, Shouyang Wang, Kin Keung Lai
BMCBI
2007
144views more  BMCBI 2007»
13 years 7 months ago
Spectral estimation in unevenly sampled space of periodically expressed microarray time series data
Background: Periodogram analysis of time-series is widespread in biology. A new challenge for analyzing the microarray time series data is to identify genes that are periodically ...
Alan Wee-Chung Liew, Jun Xian, Shuanhu Wu, David K...
INFORMATICALT
2000
82views more  INFORMATICALT 2000»
13 years 7 months ago
Recursive Algorithms of Time Series Observations Recognition
Abstract. The paper presents new method for sequential classification of the time series observations. Methods and algorithms of sequential recognition are obtained on the basis of...
Edward Shpilewski
MOR
2006
73views more  MOR 2006»
13 years 7 months ago
Permuted Standardized Time Series for Steady-State Simulations
We describe an extension procedure for constructing new standardized time series procedures from existing ones. The approach is based on averaging over sample paths obtained by per...
James M. Calvin, Marvin K. Nakayama
BIOCOMP
2006
13 years 9 months ago
Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene
Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectatio...
Yu Zhang, Zhidong Deng, Hongshan Jiang, Peifa Jia