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A Hybrid Macroevolutionary Algorithm
2005Macroevolutionary algorithm (MA) is a new approach to optimization problems based on extinction patterns in macroevolution. It is different from the traditional population-level evolutionary algorithms such as genetic algorithms. In MAs, evolves at the level of higher taxa is used as the underlying metaphor.
Jihui Zhang 0003, Junqin Xu
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2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
The paper presents a new graph based clustering algorithm. Traditional clustering algorithms have the drawback that it takes large number of iterations in order to come up with the desired number of clusters. The advantage of this approach is that the size of the dataset is reduced using graph based clustering approach and the required number of ...
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The paper presents a new graph based clustering algorithm. Traditional clustering algorithms have the drawback that it takes large number of iterations in order to come up with the desired number of clusters. The advantage of this approach is that the size of the dataset is reduced using graph based clustering approach and the required number of ...
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Hybrid coevolutionary algorithms vs. SVM algorithms
Proceedings of the 9th annual conference on Genetic and evolutionary computation, 2007As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational technique is characterized as a soft computing learning method with its roots in the theory of evolution.
Rui Li 0083 +2 more
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DHPTID-HYBRID Algorithm: A Hybrid Algorithm for Association Rule Mining
2010Direct Hashing and Pruning algorithm of ARM performs well at initial passes by smaller candidate 2-itemset generation and turns out to be very powerful to facilitate initial itemset generation. Efficient pruning technique of AprioriTid algorithm is highly effective for frequent itemset generation in the later passes.
Shilpa Sonawani, Amrita Mishra
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A simplex genetic algorithm hybrid
Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97), 2002One of the main obstacles in applying genetic algorithms (GAs) to complex problems has been the high computational cost due to their slow convergence rate. To alleviate this difficulty, we developed a hybrid approach that combines a GA with a stochastic variant of the simplex method in function optimization. Our motivation for developing the stochastic
John Yen, Bogju Lee
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A hybrid algorithm for continuous optimisation
2009 IEEE Congress on Evolutionary Computation, 2009An effective particle swarm - quasi-Newton hybrid for the optimisation of continuous functions is developed, which is shown to work well on a range of test problems. This method exploits the global exploration abilities of the PSO algorithm and the fast convergence of the quasi-Newton method.
Nathan Thomas, Martin Reed 0002
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A Hybrid Algorithm for Global Optimization
2015 11th International Conference on Computational Intelligence and Security (CIS), 2015In this paper, a hybrid optimization algorithm, consisting of a central force optimization and a gradient-based method, is constructed. The central force optimization is used to locate decent points for previously converged local minima. The combined algorithm balance explores and exploits.
Fei Qin, Jie Liu
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Simplified hybrid fireworks algorithm
Knowledge-Based Systems, 2019Abstract As a relatively new swarm intelligence algorithm, the fireworks algorithm (FWA) has been applied to solve lots of real-world optimization problem. However, there are still some shortcomings in the FWA algorithms. The search equation of FWA is relatively simple.
Yonggang Chen +5 more
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Hybrid Genetic Algorithm for TSP
2011 Seventh International Conference on Computational Intelligence and Security, 2011When use simple genetic algorithm for solving the traveling salesman problem, the generated optimal solution is over stochastic and does not consider the neighborhood information in whole search process. In order to reduce the randomness, the paper proposes a hybrid genetic algorithm which based on ant algorithm that making better use of the ...
Lai Nian, Jinhua Zheng
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A Hybrid Evolutionary Algorithm for CSP
2004In this paper, we present a new framework for combining complete and incomplete methods in order to solve constraint satisfaction problems. This algorithm scheme uses constraint propagation techniques and local search heuristics embedded in an evolutionary computation context. The uniformity of the involved structures provides an harmonious interaction
Barichard, Vincent +3 more
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