Robust Principal Component Analysis (RPCA), which is a popular parsimony model, is becoming increasingly important for researchers to do data analysis and prediction. The RPCA formulation is made of two components: sp...
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To solve reliability-based robust design optimization (RBRDO) problem in engineering practice, it requires repeated performance of actual complex computation-intensive model simulation within the nesting optimization....
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To solve reliability-based robust design optimization (RBRDO) problem in engineering practice, it requires repeated performance of actual complex computation-intensive model simulation within the nesting optimization. In order to improve the computation efficiency, this paper presents an improved formulation of the RBRDO, based on which the RBRDO problem is transformed into approximate sequential sub-optimization problems (ASSOP). In the outer optimization, a fast method to calculate the performance-measure-approach (PMA) functions in ASSOP is introduced, which only needs adaptive limited computation number of the actual simulation models. In the inner optimization, the PMAs in each sub-optimization problem are further expressed as the explicit functions of design vectors, which make each sub-optimization problem deterministic and accelerate the computation speed without performing the actual complex computation-intensive model simulation. Numerical examples shows that the above method is quite efficient since it can effectively reduce the computation number of the actual simulation model and the method itself is applicable to integrate into the existing commercial software such as finite element software. Hence, the method presented in this paper is of high application value to solve complex RBRDO problems in engineering practice.
Considering the fraudulent behavior of Quality of Service (QoS) for web services, a method to monitor the QoS deviation was proposed in this paper. Firstly, we used random variable to describe the uncertainty of QoS. ...
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This paper is concerned with finite-time chaos control of unified hyperchaotic systems with multiple parameters. Based on the finite-time stability theory in the cascade-connected systems, a nonlinear control law is p...
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The operation of splicing on words was introduced by Tom Head while proposing a theoretical model of DNA recombination. Subsequent investigations on splicing on linear and circular strings of symbols have resulted in ...
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This paper proposes a complex system optimization method to solve economic emission load dispatch. First, a real-world economic emission load dispatch is modeled as a complex system problem, and the optimization objec...
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This paper proposes a complex system optimization method to solve economic emission load dispatch. First, a real-world economic emission load dispatch is modeled as a complex system problem, and the optimization objectives include economic load dispatch, emission load dispatch and transmission network loss. Then a called BBO/complex method is introduced, which extends biogeography-based optimization to a multi-archipelago environment to suit the structure of complex systems. Finally, the proposed method is applied to the economic emission load dispatch, and the results show that it can obtain good performance for economic emission load dispatch studied in this paper, and it is a competitive algorithm for solving complex system optimization problem.
Although the distance between binary codes can be computed fast in Hamming space, linear search is not practical for large scale datasets. Therefore attention has been paid to the efficiency of performing approximate ...
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Although the distance between binary codes can be computed fast in Hamming space, linear search is not practical for large scale datasets. Therefore attention has been paid to the efficiency of performing approximate nearest neighbor search, in which hierarchical clustering trees (HCT) are widely used. However, HCT select cluster centers randomly and build indexes with the entire binary code, this degrades search performance. In this paper, we first propose a new clustering algorithm, which chooses cluster centers on the basis of relative distances and uses a more homogeneous partition of the dataset than HCT has to build the hierarchical clustering trees. Then, we present an algorithm to compress binary codes by extracting distinctive bits according to the standard deviation of each bit. Consequently, a new index is proposed using compressed binary codes based on hierarchical decomposition of binary spaces. Experiments conducted on reference datasets and a dataset of one billion binary codes demonstrate the effectiveness and efficiency of our method.
Recent advances in visual tracking have focused on handling deformations and occlusions using the part-based appearance model. However, it remains a challenge to come up with a reliable target representation using loc...
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In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorith...
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In this paper, we survey recent approaches to blue-noise sampling and discuss their beneficial applications. We discuss the sampling algorithms that use points as sampling primitives and classify the sampling algorithms based on various aspects, e.g., the sampling domain and the type of algorithm. We demonstrate several well-known applications that can be improved by recent blue-noise sampling techniques, as well as some new applications such as dynamic sampling and blue-noise remeshing.
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