Multi-Population Multi-Objective Cultural Algorithm

Guo, Yinan; Cao, Yuan; Liu, Dan Dan

doi:10.4028/www.scientific.net/amr.156-157.52

Cited by 2 publications

(1 citation statement)

References 6 publications

(6 reference statements)

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“…Ochoa et al [29] provide a solution of Logistics Service Based on Data Mining in combination with cultural algorithm, and applied it in optimization of distribution of vehicles within a city. A multi-population multi-objective cultural algorithm adopting knowledge migration is proposed by Guo et al, [30] and has been applied to function optimization problems. Reynolds and Liu [31] propose an extension of Cultural Algorithms for Multi-Objective optimization, MOCAT that fully utilizes all of the available categories of knowledge sources and has been applied to function optimization problem.…”

Section: A Short Survey Of Cultural Algorithmmentioning

confidence: 99%

Nugget Discovery with a Multi-Objective Cultural Algorithm

Srinivasan¹

2012

CSEIJ

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Partial classification popularly known as nugget discovery comes under descriptive knowledge discovery. It involves mining rules for a target class of interest. Classification "If-Then" rules are the most sought out by decision makers since they are the most comprehensible form of knowledge mined by data mining techniques. The rules have certain properties namely the rule metrics which are used to evaluate them. Mining rules with user specified properties can be considered as a multi-objective optimization problem since the rules have to satisfy more than one property to be used by the user. Cultural algorithm (CA) with its knowledge sources have been used in solving many optimization problems. However research gap exists in using cultural algorithm for multi-objective optimization of rules. In the current study a multi-objective cultural algorithm is proposed for partial classification. Results of experiments on benchmark data sets reveal good performance.

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Section: A Short Survey Of Cultural Algorithmmentioning

confidence: 99%

Nugget Discovery with a Multi-Objective Cultural Algorithm

Srinivasan¹

2012

CSEIJ

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A hybrid agent based virtual organization for studying knowledge evolution in social systems

Srinivasan¹,

Ramakrishnan

2012

AIR

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Social modeling applies computational methods and techniques to the analysis of social processes and human behavior. Cultural algorithms (CA's) are evolutionary systems which utilize agent technology and which supports any evolutionary strategy like genetic algorithm, evolutionary algorithm or swarm intelligence or ant algorithms. CA's have been used for modeling the evolution of complex social systems, for re-engineering rule based systems, for data mining, and for solving optimization problems. In the current study a cultural algorithm framework is used to model an Agent Based Virtual Organization (ABVO) for studying the dynamics of a social system at micro as well as macro level. Research gap exists in defining a concrete and systematic method for evaluating and validating Agent Based Social Systems (ABSS). Also the knowledge evolution process at micro and macro levels of an organization needs further exploration. The proposed CA is applied to the problem of multi-objective optimization (MOO) of classification rules. The evolutionary knowledge produced by the agents in creating the rules is accepted into the belief space of the CA and macro evolution takes place. The belief space in turn influences the agents in successive generations. The rules created by the individuals and the knowledge sources created during evolution provide a concrete method to evaluate both the individuals as well as the whole social system. The feasibility of the system has been tested on bench mark data sets and the results are encouraging.

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Multi-Population Multi-Objective Cultural Algorithm

Cited by 2 publications

References 6 publications

Nugget Discovery with a Multi-Objective Cultural Algorithm

Nugget Discovery with a Multi-Objective Cultural Algorithm

A hybrid agent based virtual organization for studying knowledge evolution in social systems

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