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Differential Evolution (DE) is one of the current best evolutionary algorithms. It becomes the popular research topic in many fields such as evolutionary computing and intelligent optimization. At present, DE has successfully been applied to diverse domains of science and engineering, such as signal processing, neural network optimization, pattern recognition, machine intelligence, chemical engineering...
The object tracking by using single feature is possible to generate errors and easy to lose the target if the illumination and object size scale are changed. We propose a particle-filter-object-tracking algorithm. The proposed algorithm is based on a covariance region descriptor (CRD). The CRD can fuse different features of a targeted object region while handling various complex backgrounds. Hence,...
The photographic map is one important kind of maps with the ground digital photographic map. There are many researchers do the research on digital vector map but very few about photographic map. And these photographic map watermark algorithms are based on improved image features digital watermark algorithms, which have some faults influencing the watermark information. To resolve this problem a new...
Due to the limited availability of energy within network nodes, energy-efficient routing mechanism is one of the most critical issues in wireless sensor networks. In this paper, we propose a multi-path routing algorithm with energy-aware based on ant colony system. The algorithm introduces three improved rules: Ant Marginalization Rule, State Transition Rule and Global Pheromone Update Rule to solve...
The characteristics of publish/subscribe technology are of asynchronism and loosely coupled. This phenomenon makes producers and consumers are de-communicated in temporal and spatial domains during processing. It requires develop a dynamic integration in today's large-scale, distributed information system. This paper introduces a Semantic Integration Data Model (SIDM) for publish/subscribe systems,...
This paper presents an implementation of incremental tumor diagnosis algorithm (ITDA) on microarray data for improving diagnostic accuracy of tumor. A classifier (BP or KNN) was used in the algorithm to estimate confidences of a new unlabeled sample in different classes. When one confidence is higher than the threshold, the sample will be labeled; otherwise, the sample will be diagnosed by medical...
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