C. Bracken, B. Rajagopalan, & E. Zagona (2014). “A Hidden Markov Model Combined with Climate Indices for Multi-decadal Streamflow Simulation,” Water Resources Research, 50, 7836-7846. Abstract: ...
Hidden Markov models (HMMs) provide a robust statistical framework for analysing sequential data by assuming that the observed processes are driven by underlying, unobserved states. These models have ...
Drought is a naturally occurring climate phenomenon that significantly affects human and environmental activity, and can be considered one of the most widespread and destructive natural disasters.
Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 62, No. 1 (2000), pp. 57-75 (19 pages) Hidden Markov models form an extension of mixture models which provides a ...
Sparse early-stage data limits accurate geological risk assessment, increasing the chance of undetected hazards ahead of the TBM. By integrating borehole-derived information through an observation ...
The amino acid sequence of the transmembrane protein and its corresponding positions on the cell membrane are transformed into a hidden Markov process. After evaluating the parameters, the Viterbi ...
Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those ...
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