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Canonical correlation analysis(CCA) is a popular technique that works for finding the correlation between two sets of variables. However, CCA faces the problem of small sample size in dealing with high dimensional data. Several approaches have been proposed to overcome this issue, but the resulting transformation matrix fails to extract shared structures among data samples. In this paper, we propose...
The pseudosolubilized medium-chain-length n -alkanes during biodegradation process, and optimization of medium composition and culture conditions for rhamnolipid production by Pseudomonas sp. DG17 using Plackett–Burman design and Box–Behnken design, were examined in this study. The results showed that pseudosolubilized concentration of C 14 to C 20...
Establishing the evaluation mechanism of construction enterprises is helpful to regular the order of construction market. But there will occur some residual problem, such as construction period postpone, economic loss of the proprietor, handing over project, claims and so on. In this paper, some measures are put forward to overcome such problems, and will be in favor to the establishing of the evaluation...
K-harmonic means clustering algorithm (KHM) is a center-based like K-means (KM), which uses the harmonic averages of the distances from each data point to the centers as components to its performance function and overcomes KM's one major drawback that is highly dependent on the initial identification of elements that represent the clusters. However, KHM is also easily trapped in local optima. In this...
In order to recognize stratums, a new support vector machine model (SVMM) is built on the basis of well-logging data and with RBF as its kernel function. Through the optimization of penalty parameter C and the introduction of a discriminant function, the classification accuracy of SVMM is greatly enhanced. Experiments show that the SVM classifier can be applied effectively to the recognition of stratums,...
In order to overcome the disadvantage that only one solution can be found in particle swarm optimization (PSO), a novel niche particle swarm multi_optimizer (multi_PSOer) which combines two strategies is devised in this paper. Firstly, guaranteed convergence PSO (GCPSO) is adopted to guarantee the algorithm can converge on a local point. Secondly, niche technique is used to ensure the algorithm is...
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