Titlebook: Intelligent Data Engineering and Automated Learning - IDEAL 2006; 7th International Co Emilio Corchado,Hujun Yin,Colin Fyfe Conference proc

FRET

Time Series Relevance Determination Through a Topology-Constrained Hidden Markov Modelod for Generative Topographic Mapping Through Time, a topology-constrained Hidden Markov Model that performs simultaneous time series data clustering and visualization. This relevance determination method can be used as a basis for time series selection, and should ease the interpretation of the time series clustering results.

obsession

分貝

規(guī)范就好

Process State and Progress Visualization Using Self-Organizing Maplant simulator data. One aim is to depict only the most relevant information of the process so that interpretating process behaviour would become easier for plant operators. In our experiments, the method was able to detect a leakage situation in an early stage and it was possible to observe how the system changed its state as time went on.

混雜人

糾纏

Generalization Performance of Exchange Monte Carlo Method for Normal Mixture Modelsd is appropriate for the Bayesian learning in singular learning machines, and experimentally show that it provides better generalization performance in the Bayesian learning of a normal mixture model than the conventional Monte Carlo method.

CLAIM

楓樹(shù)

下船

A More Effective Constructive Algorithm for Permutation Flowshop Problemmeasure. Computational results show that the measure is effective and NEH-D is better than PE-VM. There is one parameter in NEH-D, and we design an experiment to try to find a near optimized value of it for tuning the performance of NEH-D.