We present a particle swarm optimization algorithm OT-PSO using orthogonal test technique. Based on the classical PSO, OT-PSO searches for local optimum in the neighbor area of the global best solution by using the me...
详细信息
The challenges for building the component-based software architecture are how to estimate the assembly of reusable software components and make the properties forecast to the associated architecture. To address these ...
详细信息
A new method for constructing phylogenetic trees from a given set of objects (proteins, species , etc.) is presented. The method bisects the set of gene sequences so that the sequences within one subset have most simi...
详细信息
In this paper, an incremental outlier detection technique capable of dealing with a large amount of data is presented and evaluated in the context of intrusion detection. The proposed method is based on the LOcal Corr...
详细信息
ISBN:
(纸本)9781605581668
In this paper, an incremental outlier detection technique capable of dealing with a large amount of data is presented and evaluated in the context of intrusion detection. The proposed method is based on the LOcal Correlation Integral (LOCI for short). The detection technique consists of two parts. The first part named insertion receives the sequence of input point and updates Multi-granularity DEviation Factor (MDEF) of the point at intervals. The second part named deletion deletes one or a batch of points. This technique is able to process streaming data in a single scan. Moreover, the number of updates in the incremental LOCI algorithm per insertion/deletion of a single data record does not depend on the total number of data records. Experimental results with real life data sets show that the technique is capable of dealing with data streams, successfully detecting outlier. Copyright 2009 ACM.
Soft sensing is usually presented as a constraint solving problem. In a manufacturing context, traditional methods of soft sensing have to face challenges in robustness and efficiency. In this paper, we proposed a gra...
详细信息
ISBN:
(纸本)9781605581668
Soft sensing is usually presented as a constraint solving problem. In a manufacturing context, traditional methods of soft sensing have to face challenges in robustness and efficiency. In this paper, we proposed a granular-based approach to constraint solving for soft sensing. In our method, we first construct a granular-based soft sensing model, then estimate bounds of each granule, and finally solve this granulated problem with a smaller size. According to our analysis, this method is robust and efficient. Copyright 2009 ACM.
In modern process industry, it is often difficult to analyze a manufacture process due to its numerous time-series data. Analysts wish to not only interpret the evolution of data over time in a working procedure, but ...
详细信息
This paper presents a component-based model with a novel ranking method (CMR) for constrained evolutionary optimization. In general, many constraint-handling technique inevitably solve two important problems: (1) how ...
详细信息
To preserve the sharp features and details of the synthetic aperture radar (SAR) image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform ...
详细信息
To preserve the sharp features and details of the synthetic aperture radar (SAR) image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform (NSBT) domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture (BLS-GSM).
Quay crane scheduling problem is a very important multi resource scheduling problem in container terminals. This paper gives the general model of quay crane scheduling and introduces a heuristic method Ant Colony Opti...
详细信息
A modified Fisher discriminate analysis method for classifying stream data is presented. To satisfy the real-time demand in classifying stream data, this method defines a new criterion for Fisher discriminate analysis...
详细信息
暂无评论