Fusion of Learning Automata to Optimize Multi-constraint Problem
Journal Title: Journal of Information Systems and Telecommunication - Year 2015, Vol 3, Issue 1
Abstract
This paper aims to introduce an effective classification method of learning for partitioning the data in statistical spaces. The work is based on using multi-constraint partitioning on the stochastic learning automata. Stochastic learning automata with fixed or variable structures are a reinforcement learning method. Having no information about optimized operation, such models try to find an answer to a problem. Converging speed in such algorithms in solving different problems and their route to the answer is so that they produce a proper condition if the answer is obtained. However, despite all tricks to prevent the algorithm involvement with local optimal, the algorithms do not perform well for problems with a lot of spread local optimal points and give no good answer. In this paper, the fusion of stochastic learning automata algorithms has been used to solve given problems and provide a centralized control mechanism. Looking at the results, is found that the recommended algorithm for partitioning constraints and finding optimization problems are suitable in terms of time and speed, and given a large number of samples, yield a learning rate of 97.92%. In addition, the test results clearly indicate increased accuracy and significant efficiency of recommended systems compared with single model systems based on different methods of learning automata.
Authors and Affiliations
Sara Motamed, Ali Ahmadi
On-road Vehicle detection based on hierarchical clustering using adaptive vehicle localization
Vehicle detection is one of the important tasks in automatic driving. It is a hard problem that many researchers focused on it. Most commercial vehicle detection systems are based on radar. But these methods have some pr...
A New Approach to the Quantitative Measurement of Software Reliability
Nowadays software systems have very important role in a lot of sensitive and critical applications. Sometimes a small error in software could cause financial or even health loss in critical applications. So reliability a...
Node to Node Watermarking in Wireless Sensor Networks for Authentication of Self Nodes
In order to solve some security issues in Wireless Sensor Networks (WSNs), node to node authentication method based on digital watermarking technique for verification of relative nodes is proposed. In the proposed method...
A New Approach to Overcome the Count to Infinity Problem in DVR Protocol Based on HMM Modelling
Due to low complexity, power and bandwidth saving Distance Vector Routing has been introduced as one of the most popular dynamic routing protocol. However, this protocol has a serious drawback in practice called Count To...
GoF-Based Spectrum Sensing of OFDM Signals over Fading Channels
Goodness-of-Fit (GoF) based spectrum sensing of orthogonal frequency-division multiplexing (OFDM) signals is investigated in this paper. To this end, some novel local sensing methods based on Shapiro-Wilk (SW), Shapiro-F...