Open AccessJournal Article
A self-organizing channel assignment algorithm: A cellular learning automata approach
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A cellular learning automata based self-organizing channel assignment algorithm is introduced and the simulation results show that the micro-cellular network canSelf-organize by using simpleChannel assignment algorithm as the network operates.Abstract:
Introduction of micro-cellular networks offer a potential increase in capacity of cellular networks, but they create problems in management of the cellular networks. A solution to these problems is self-organizing channel assignment algorithm with distributed control. In this paper, we first introduce the model of cellular learning automata in which learning automata are used to adjust the state transition probabilities of cellular automata. Then a cellular learning automata based self-organizing channel assignment algorithm is introduced. The simulation results show that the micro-cellular network can self-organize by using simple channel assignment algorithm as the network operates.read more
Citations
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A mathematical framework for cellular learning automata
TL;DR: This paper first provides a mathematical framework for cellular learning automata and then studies its convergence behavior, showing that for a class of rules, called commutative rules, the cellularlearning automata converges to a stable and compatible configuration.
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A Multi-Objective PMU Placement Method Considering Measurement Redundancy and Observability Value Under Contingencies
TL;DR: In this article, a multi-objective phasor measurement unit (PMU) placement method was proposed for electric transmission grids. And the resultant optimization problem was solved using Cellular Learning Automata (CLA), introducing new CLA local rules to improve the optimization process.
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Cellular Learning Automata With Multiple Learning Automata in Each Cell and Its Applications
TL;DR: It is shown that, for a class of rules called commutative rules, the CLA model converges to a stable and compatible configuration and two applications of this new model such as channel assignment in cellular mobile networks and function optimization are given.
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Application of heuristic algorithms to optimal PMU placement in electric power systems: An updated review
TL;DR: In this paper, the authors provided a literature review on different heuristic optimization methods to solve the optimal PMU placement (OPP) problem and compared with different points of views.
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A Cellular Learning Automata Based Clustering Algorithm for Wireless Sensor Networks
TL;DR: The results of experiments have shown that the proposed clustering algorithm outperforms existing clustering methods in terms of quality of clustering measured by the total number of clusters, the number of sparse clusters and the remaining energy level of the cluster heads.
References
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Book
Learning Automata: An Introduction
TL;DR: From the combination of knowledge and actions, someone can improve their skill and ability and this learning automata an introduction tells you that any book will give certain knowledge to take all benefits.
Journal ArticleDOI
Channel assignment schemes for cellular mobile telecommunication systems: a comprehensive survey
I. Katzela,Mahmoud Naghshineh +1 more
TL;DR: This article provides a detailed discussion on reuse partitioning schemes, the effect of handoffs, and prioritization schemes, and other important issues in resource allocation such as overlay cells, frequency planning, and power control.
Journal ArticleDOI
Two-dimensional cellular automata
TL;DR: A largely phenomenological study of two-dimensional cellular automata is reported, finding Qualitative classes of behavior similar to those in one-dimensional Cellular automata are found.
Journal ArticleDOI
Graph partitioning using learning automata
B.J. Oommen,E.V. de St. Croix +1 more
TL;DR: This work proposes the first reported learning automaton based solution to the uniform graph partitioning problem, and believes that it is the fastest algorithm reported to date.
Journal ArticleDOI
Continuous learning automata solutions to the capacity assignment problem
B.J. Oommen,T.D. Roberts +1 more
TL;DR: In this paper, a new method which uses continuous learning automata to solve the capacity assignment problem is introduced. But, the authors assume that the traffic consists of different classes of packets with different average packet lengths and priorities.