Comparison of Ant Colony, Elite Ant system and Maximum – Minimum Ant system Algorithms for Optimizing Coefficients of Sediment Rating Curve (Case Study: Sistan River)
Authors
Abstract:
By far, different models for determining the relationship between the flow rate and amount of precipitation have been developed. many models are based on regression models with limited assumptions. one of the most common methods for estimating sediment of rivers is sediment rating curve. for better estimation of the amount of sediment based of sediment curve rating equation, it is possible to optimize its coefficients. this estimation of flow rate , which is much easier than measuring sediment rate, provides more prices and accurate estimation of sediment rate.
similar resources
comparison of ant colony, elite ant system and maximum – minimum ant system algorithms for optimizing coefficients of sediment rating curve (case study: sistan river)
by far, different models for determining the relationship between the flow rate and amount of precipitation have been developed. many models are based on regression models with limited assumptions. one of the most common methods for estimating sediment of rivers is sediment rating curve. for better estimation of the amount of sediment based of sediment curve rating equation, it is possible t...
full textAnt Colony System Optimization
Successful heuristic algorithms for solving combinatorial optimization problems have mimicked processes observed in nature. Two highly successful families of algorithms that do this are simulated annealing and genetic algorithms. Here, a third family of algorithms, ant colony optimization is explored and implemented in C#. The test bed for evaluating the quality of solutions is based on several...
full textRecruiting Ant Colony System
We briefly describe an approach to extend the Ant Colony System by a group recruitment strategy. The underlying idea is very similar to the behavior of real ants, which use e.g. tandem-techniques to guide each other to large food sources. General investigations with small and medium sized colonies have shown that such strategies in combination with mass recruitment (pheromones) increase the foo...
full textMulti Colony Ant Algorithms
In multi colony ant algorithms several colonies of ants cooperate in finding good solutions for an optimization problem. At certain time steps the colonies exchange information about good solutions. If the amount of exchanged information is not too large multi colony ant algorithms can be easily parallelized in a natural way by placing the colonies on different processors. In this paper we stud...
full textA New Ant Colony Optimization Algorithm: Three Bound Ant System
Since its introduction, ant colony optimization (ACO) algorithms and especially the MAX-MIN ant system (MMAS) [4] are found to be well suited for many challenging optimization problems. Our theoretical analyses of MMAS allowed us to create the new algorithm, named the three bound ant system (TBAS), which has lower computational complexity and at the same time retains and even improves the quali...
full textDACS3:Embedding Individual Ant Behavior in Ant Colony System
Ants are fascinating creatures that demonstrate the ability to find food and bring it back to their nest. Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). The principle of cooperation forms the backbone of such algorithms, commonly used to find solutions to problems such as the Traveling Salesman Problem (TSP)...
full textMy Resources
Journal title
volume 1 issue None
pages 55- 66
publication date 2014-12
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023