NDLI: Meta-controlled Boltzmann machine: Its convergence and application to power system

Content Provider	IEEE Xplore Digital Library
Author	Watada, Junzo Haydee Rocio Melo Cisneros
Copyright Year	2012
Description	Author affiliation: Graduate School of Information, Production and System, Waseda University, 2-7 Hibikino, Wakamatsu, Kitakyushu 808-0135 Japan (Watada, Junzo; Haydee Rocio Melo Cisneros)
Abstract	In this paper, meta controlled Boltzmann machine; the double-layered Boltzmann machine consisting of upper (Hopfield network) and lower (Boltzmann network) layers, is built and the double-layered Boltzmann machine is proved to converge the optimal solution, after then, is efficiently applied to solve the investment problem to power system where the problem is understood as mean-variance problem using mathematical programming with two objectives: the minimization of risk and the maximization of expected return. The proposed method is applied both diffusion processes and simulated annealing. The convergence proof of the proposed method is showed in this paper. Meta-controlled Boltzmann machine shows an ability to solve combinatorial optimization problems better than either Hopfield networks or Boltzmann machines.
Starting Page	1
Ending Page	6
File Size	352663
Page Count	6
File Format	PDF
ISBN	9781467344975
ISSN	21544824
e-ISBN	9781889334479
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-24
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	TSI Press
Subject Keyword	Equations Mathematical model Convergence Neurons Substations Investments Noise
Content Type	Text
Resource Type	Article

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