Hidden Markov Model

Softcomputing techniques play a vital role in the industry. This book presents several important papers presented by some of the well-known scientists from all over the globe. The application domains discussed in this book include: agroecology, bioinformatics, branched fluid-transport network layout design, dam scheduling, data analysis and exploration, detection of phishing attacks, distributed terrestrial transportation, fault detection of motors, fault diagnosis of electronic circuits, fault diagnosis of power distribution systems, flood routing, hazard sensing, health care, industrial chemical processes, knowledge management in software development, local multipoint distribution systems, missing data estimation, parameter calibration of rainfall intensity models, parameter identification for systems engineering, petroleum vessel mooring, query answering in P2P systems, real-time strategy games, robot control, satellite heat pipe design, monsoon rainfall forecasting, structural design, tool condition monitoring, vehicle routing, water network design, etc.

This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics.

This volume takes you on a fascinating journey into the world of math and its many uses. Experts in the field show how math can solve real-world problems, from managing inventories to making decisions. You'll also learn about things like optics and programming.

Have You Ever Wondered How Artificial Intelligence And Data Science Work? Are you looking to learn about machine learning and how it relates to these topics??

Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearn