Results 221 to 230 of about 177,417 (264)

A Hybrid Clustering Algorithm

2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009
In view of the fact that DBSCAN clustering algorithm can identify the data with arbitrary shape and one-pass clustering algorithm has the quick and efficient feature, this paper proposes a two-stage hybrid clustering algorithm. DBSCAN is improved to process the data with categorical attributes.
Sheng-Yi Jiang, Xia Li
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A Hybrid Macroevolutionary Algorithm

2005
Macroevolutionary 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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Hybrid Multifluid Algorithms

SIAM Journal on Scientific Computing, 1996
A hybrid approach is presented for computing the dynamics of compressible multicomponent fluids, which is based on augmenting the Euler multicomponent equations by the pressure evolution equation. The extended system offers two choices for updating the pressure field: that is a conservative update, making use of the equation of state applied throughout
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Hybrid clustering algorithm

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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DHPTID-HYBRID Algorithm: A Hybrid Algorithm for Association Rule Mining

2010
Direct 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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Hybrid coevolutionary algorithms vs. SVM algorithms

Proceedings of the 9th annual conference on Genetic and evolutionary computation, 2007
As 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, Bir Bhanu, Krzysztof Krawiec   +2 more
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A simplex genetic algorithm hybrid

Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97), 2002
One 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, 2009
An 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), 2015
In 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, 2019
Abstract 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, Lixiang Li 0001, Xinchao Zhao, Jinghua Xiao, Qingtao Wu, Ying Tan 0002   +5 more
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