Software is everywhere. However, software is not always trustworthy. Confronting the demand of software trustworthiness evaluation, this paper proposes a novel software trustworthiness evaluation approach based on com...
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To study two-tier supply chain scheduling models comprised by multi suppliers and multi manufacturers, the scheduling optimization theory is applied into the supply chain domain. A math model is built by taking the mi...
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To study two-tier supply chain scheduling models comprised by multi suppliers and multi manufacturers, the scheduling optimization theory is applied into the supply chain domain. A math model is built by taking the minimization of total flow time of work pieces and total cost of delivery as optimization objectives. The dynamic programming algorithm is used to solve the problem based on analyzing the features of its optimum solution. Multi-objectives fusion is realized through analytic hierarchy process in the algorithm iterative process. The feasibility of this model and algorithm is illustrated by a numerical example.
This paper considers the uniform parallel machine scheduling problem with unequal release dates and delivery times to minimize the maximum completion *** this NP-hard problem,the largest sum of release date,processing...
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This paper considers the uniform parallel machine scheduling problem with unequal release dates and delivery times to minimize the maximum completion *** this NP-hard problem,the largest sum of release date,processing time and delivery time first rule is designed to determine a certain machine for each job,and the largest difference between delivery time and release date first rule is designed to sequence the jobs scheduled on the same machine,and then a novel algorithm for the scheduling problem is *** evaluate the performance of the proposed algorithm,a lower bound for the problem is *** accuracy of the proposed algorithm is tested based on the data with problem size varying from 200 jobs to 600 *** computational results indicate that the average relative error between the proposed algorithm and the lower bound is only 0.667%,therefore the solutions obtained by the proposed algorithm are very accurate.
The fractal dimension based clustering ensembles algorithm was studied. It introduced clustering algorithm based on fractal dimension at first in order to create partitions for clustering ensembles, then using voting ...
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The fractal dimension based clustering ensembles algorithm was studied. It introduced clustering algorithm based on fractal dimension at first in order to create partitions for clustering ensembles, then using voting strategy to get ensembles result. Finally, an idea on distributed clustering ensembles under cloud computing environment was brief discussed. Fractal dimension based clustering ensembles algorithm can offer better solutions in terms of robustness, novelty and stability than the single clustering algorithm based on fractal dimension. Combining the approaches based on grid and fractal, the clustering algorithm called grid and fractal dimension based clustering algorithm (GFDC) was presented to create partitions for clustering ensembles instead of clustering algorithm based on fractal dimension. GFDC is able to capture arbitrary shapes and non-neighboring clustering and can be applied to the massive and high-dimension dataset.
Fractal data mining technology is based on the fractal characteristic of data set, the real data set usually exists approximate fractal characteristic in the fractal non-scaling interval. Fractal dimension can describ...
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Workflow mining is a concept in early era, it analyzes the workflow log in the control flow dimensions, to mining the actual process model, but ignores relationships among executors in workflow, hence it fails to effe...
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In order to solve the problem of high dimension in text classification, the paper proposes a method based on manifold learning and Bagging for text classification which imports manifold learning algorithm for dimensio...
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Nowadays, more and more large IT projects need to unit several entities to accomplish together, which forms project-oriented and geographically distributed virtual organizations and leads to new distributed risks. Thi...
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This paper constructs the background value of grey GM (1, 1) model by using Gaussian quadrature formula, improves its accuracy and the data quality. It indicates that reconstruction of the background value is the key ...
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This paper constructs the background value of grey GM (1, 1) model by using Gaussian quadrature formula, improves its accuracy and the data quality. It indicates that reconstruction of the background value is the key factor affecting prediction accuracy and applicability.
There are lots of performance bottlenecks for real-time queries in mass data. Many methods can only improve the efficiency for frequently used queries, but it is not advisable to neglect the non-frequently used querie...
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