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http://localhost:80/xmlui/handle/123456789/7430Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Bhattacharya, Debnath | - |
| dc.contributor.author | Das, Poulomi | - |
| dc.contributor.author | Bandopadhyay, Samir Kumar | - |
| dc.date.accessioned | 2023-03-30T06:45:33Z | - |
| dc.date.available | 2023-03-30T06:45:33Z | - |
| dc.date.issued | 2006-08 | - |
| dc.identifier.uri | http://172.16.0.4:8085/heritage/handle/123456789/7430 | - |
| dc.description.abstract | Ant Colony Optimization and Swarm Optimization are the classical areas of researches in the field of Computer Science. Computer Scientists are trying to map the Biological and Natural Solution with the Artificial one, since last 2 decades. Finally, Genetic Algorithm (GA), Genetic Programming (GP) and Artificial Neural Network (ANN), ACO[13], etc were derived from the Biological, Genetical and Natural characteristics of the living organisms.We have developed a population based stochastic optimization technique inspired by social behavior of Mosquito (Female). This research will open a new side of 'Particle Swarm Optimization', in future. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | ACM Digital Library | en_US |
| dc.relation.ispartofseries | Vol : 7;Issue :33 | - |
| dc.title | MOSQUITO ATTACK OPTIMIZATION | en_US |
| dc.title.alternative | (In) Ubiquity : Information everywhere | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Computer Science And Engineering (Publications) | |
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