• Smart Media Journal
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• v.5 no.2
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• pp.84-89
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• 2016

For a place-recommendation model based on user's behavior and multi-attribute attitude in this thesis. We focus groups that show similar patterns of visiting restaurants and then compare one and the other. We make use of The Fishbein Equation, Pearson's Correlation Coefficient to calculate multi-attribute attitude scores. Furthermore, We also make use of Preference Prediction Algorithm and Distance based method named "Euclidean Distance" to provide accurate results. We can demonstrate how excellent this system is through several experiments carried out with actual data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.6
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• pp.1251-1255
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• 2011

In this paper, we propose an optimal path search algorithm that contains all nodes using genetic algorithm. An object in this approach is formed as an equation related with the Euclidean distance between an intermediate node and the starting node and between an intermediate node and the goal node. Like other genetic algorithm structures, our algorithm defines a fitness function and selects a crossover spot node and a bitwise crossover point. A new node out of such operation survives only if it satisfies the fitness criteria and that node then becomes the starting node for the next generation. Repetition continues until no changes are made in the population. The efficiency of this proposed approach is verified in the experiment that it is better than two other contestants - sequential approach and the random approach.

• Journal of Advanced Navigation Technology
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• v.10 no.4
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• pp.371-376
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• 2006

The initial radius of sphere decoder has great effect on the bit error rate performance and computational complexity. Until now, it has been determined either by considering the statistical property of channel or by using of MMSE solution. The initial radius obtained by using statistical property of channel includes the lattice point corresponding to the transmit signal vector with very high probability. The method using MMSE solution first calculates out the MMSE solution of the received signal, then maps the hard decision of this solution into the received signal space, and finally the distance between the mapped point and the received signal is selected as the initial radius of the sphere decoding. In this paper, we derive a simple equation for initial radius selection which uses statistical property of channel and compare it with the method using MMSE solution. To compare two methods we define new metric 'Tightness'. Through the simulation, we observe that in low and moderate SNR region, the method using MMSE solution provides more complexity reduction for decoding while in high SNR region, the method using channel statistics is better.