Modeling Idea Generation Sequences Using Hidden Markov Models

A generalization of Profile Hidden Markov Model (PHMM) using one-by-one dependency between sequences

The Profile Hidden Markov Model (PHMM) can be poor at capturing dependency between observations because of the statistical assumptions it makes. To overcome this limitation, the dependency between residues in a multiple sequence alignment (MSA) which is the representative of a PHMM can be combined with the PHMM. Based on the fact that sequences appearing in the final MSA are written based on th...

Introducing Busy Customer Portfolio Using Hidden Markov Model

Due to the effective role of Markov models in customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures. In this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. One hundred articles were identified and reviewed to find direct relevance for applying Markov models...

Using Input-Output Hidden Markov Models for the Aggregation of Performance Models

This paper describes a new idea how to use InputOutput Hidden Markov Models (IOHMMs) for the aggregation of performance models and reports about corresponding first experiments. The parameters of the IOHMM are calculated from observation sequences obtained from the input/output behaviour of the original model.

مدل سازی فضایی-زمانی وقوع و مقدار بارش زمستانه در گستره ایران با استفاده از مدل مارکف پنهان

Multi site modeling of rainfall is one of the most important issues in environmental sciences especially in watershed management. For this purpose, different statistical models have been developed which involve spatial approaches in simulation and modeling of daily rainfall values. The hidden Markov is one of the multi-site daily rainfall models which in addition to simulation of daily rainfall...

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words