A Hybrid Best-So-Far Artificial Bee Colony Algorithm - Shrimal, Gajendra
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Swarm Intelligence becomes a crucial importance for the solution of many problems which cannot be easily solved with many classical mathematical techniques. The main concern while searching for new nature based solution is population. The collective behaviour of swarm's or any individuals inspire us to develop optimization-based algorithm. Artificial Bee Colony Algorithm (ABC) is the most recent advance technique to solve many mathematical problems and engineering problems. The inspiration behind this is Nature, where problems are solved on the basis of behavior of swarms, ants, bees etc. The…mehr

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Produktbeschreibung
Swarm Intelligence becomes a crucial importance for the solution of many problems which cannot be easily solved with many classical mathematical techniques. The main concern while searching for new nature based solution is population. The collective behaviour of swarm's or any individuals inspire us to develop optimization-based algorithm. Artificial Bee Colony Algorithm (ABC) is the most recent advance technique to solve many mathematical problems and engineering problems. The inspiration behind this is Nature, where problems are solved on the basis of behavior of swarms, ants, bees etc. The foraging behavior of bees plays an important role while approaching ABC algorithms.
Autorenporträt
Gajendra Shrimal is B.E., M.Tech in field of Computer Science and Engineering. He is currently working as an Assistant Professor in Computer Engineering Department at JaganNath University, Jaipur. His area of interest includes Pattern Recognition & Image Processing, Artificial Intelligence, Randomize Algorithms, and Nature Inspired Computing.