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Stability Threshold-based Affinity Propagation and Its Application
Limin Wang,Yizhang Wang,Xuming Han,Qiang Ji 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.6
Given the performance of original affinity propagation algorithm is greatly affected by preference (P), stability threshold-based affinity propagation clustering algorithm (STAP) is proposed in this paper, including stability threshold to obtain the state of convergence when getting real class number and capture the corresponding P, and it take S-type function as damping factor to accelerate the convergence speed of STAP clustering algorithm. Besides it is successfully applied in the financial evaluation of public companies. The simulation experimental results show that, comparing the traditional affinity propagation clustering algorithm, STAP clustering algorithm can obtain high precision and fast convergence rate to improve clustering performance.
Algorithm for Detection of Fire Smoke in a Video Based on Wavelet Energy Slope Fitting
Yi Zhang,Haifeng Wang,Xin Fan 한국정보처리학회 2020 Journal of information processing systems Vol.16 No.3
The existing methods for detection of fire smoke in a video easily lead to misjudgment of cloud, fog and movingdistractors, such as a moving person, a moving vehicle and other non-smoke moving objects. Therefore, analgorithm for detection of fire smoke in a video based on wavelet energy slope fitting is proposed in this paper. The change in wavelet energy of the moving target foreground is used as the basis, and a time window of 40continuous frames is set to fit the wavelet energy slope of the suspected area in every 20 frames, thusestablishing a wavelet-energy-based smoke judgment criterion. The experimental data show that the algorithmdescribed in this paper not only can detect smoke more quickly and more accurately, but also can effectivelyavoid the distraction of cloud, fog and moving object and prevent false alarm.