The mathematics of Markov models: what Markov chains can really predict in forest successions.

By Dmitrii O. Logofet, Ekaterina V. Lesnaya. 2000

138 citations recorded by the source corpus.

Subfields: Environmental Engineering, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/20b95dc3bfc54fd77f8c6202382c66e00cb378ac

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. M. Muselli
2. Cyril Voyant
3. Marie-Laure Nivet
4. Christophe Paoli

In Global and Planetary Change

1. M. Muselli
2. Cyril Voyant
3. Marie-Laure Nivet
4. Christophe Paoli

In Nature and Landscape Conservation

1. M. Muselli
2. Cyril Voyant
3. Marie-Laure Nivet
4. Christophe Paoli

Citations in the corpus

• Forecasting of preprocessed daily solar radiation time series using neural networks (2010, methodology): “In forecasting domain, some authors have tried to use so-called Markov processes (Logofet and Lesnaya, 2000; Muselli et al., 2001), specifically the Markov chains.”
• Predicting land-cover and land-use change in the urban fringe A case in Morelia city, Mexico (2001, background): “Markov chains represent a dynamic system of special classes involving transition probabilities, described as symmetric matrices (Luenberger, 1979; Logofet and Lesnaya, 2000).”