Please use this identifier to cite or link to this item: http://dspace.dtu.ac.in:8080/jspui/handle/repository/13454
Title: OPTIMIZATION OF STATE REDUCTION FOR STOCHASTIC FINITE STATE SYSTEM
Authors: DAS, SAUMYA
Keywords: Stochastic
Reduction
Finite
Issue Date: 24-Nov-2010
Series/Report no.: TD680;66
Abstract: . In this thesis, it is the aim to gain fundamental insight into the State Reduction of Stochastic Finite State System. State reduction is carried out by an optimization process and applied for a practical case i.e. Economic load dispatch in power system. A power system problem is converted into a stochastic finite state system and its state reduction leads to fuel Cost Reduction for the Power System. The optimization Process which is used here is Particle Swarm Optimization (PSO). Although extensive research on the PSO algorithm has been conducted but understanding of the algorithm still seems lacking. In this work Fortran 77 is used to implement the algorithm of PSO. Particle swarm optimization is a stochastic, population-based computer problem-solving algorithm; it is a kind of swarm intelligence that is based on social- principles and provides insights into social behavior, as well as contributing to social-psychological engineering applications. ...
Description: ME THESIS
URI: http://dspace.dtu.ac.in:8080/jspui/handle/repository/13454
Appears in Collections:M.E./M.Tech. Electronics & Communication Engineering

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