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| 1 | 基于新型AFCM的多传感器目标跟踪航迹融合显示文摘多目标跟踪是多传感器系统信息融合中的核心技术之一。采用新型的AFCM模糊算法实现对多目标交叉状态下航迹数据关联。该算法定义了一种新的度量空间中的距离,通过新的距离定义有效抑制含有噪声点的样本及目标航迹交叉在迭代中对数据关联聚类中心点的大幅偏差。同时应用改进带加权的航迹融合算法对红外和毫米波雷达传感器测量的航迹数据进行融合。仿真试验证明,新的算法在综合多传感器探测优势的基础上,对航迹的融合结果优于SF算法。新的数据关联算法和改进的加权航迹融合算法为多源信息融合提供了一种可靠有效的多目标跟踪技术。 | 郭睿 王翔 张弛 卜春光 | 2009 | 传感技术学报2009，22，3： | 4 |
| 2 | 采用AFCM-SMOTE-RF的光伏电站故障诊断方法显示文摘光伏电站故障频发,影响发电效率。而相对于正常运行数据,电站故障数据较少,导致故障检测精度不高。针对这个问题,提出了一种基于AFCM(alter-native fuzzy C-means)-SMOTE(synthetic minority over-sampling technique)算法与随机森林算法相结合的光伏电站故障诊断方法。用AFCM-SMOTE算法对故障样本进行处理,生成“人造”样本,用“人造”样本训练随机森林算法,最终实现对光伏电站故障的检测。实验结果表明,AFCM-SMOTE算法很好地解决了随机森林在光伏故障检测应用中因为故障样本数据少导致分类不精确的问题,提高了故障诊断的准确性。 | 张治 马辉 王林 | 2021 | 电源技术2021，45，11： | 1 |
| 3 | 一种改进的AFCM聚类算法显示文摘模糊C-均值(FCM)聚类算法在图象处理和模式识别领域中得到了广泛的应用,但由于FCM算法在大数据集的情况下需要消耗大量的CPU时间而使用户感到十分不便。本文对近似的模糊C-均值(AFCM)算法进行了改进,提出了一种改进的AFCM(IAFCM)聚类算法。对一个128×128的彩色数字图象进行FCM、AFCM、IAFCM算法聚类,结果表明,IAFCM算法所用的时间约为AFCM算法的二分之一,仅为FCM算法的十三分之一。 | 刘健庄 谢维信 | 1990 | 西安电子科技大学学报1990，17，3： | 1 |
| 4 | Alternative Fuzzy Cluster Segmentation of Remote Sensing Images Based on Adaptive Genetic Algorithm显示文摘Remote sensing image segmentation is the basis of image understanding and analysis. However,the precision and the speed of segmentation can not meet the need of image analysis,due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm(AGA) and Alternative Fuzzy C-Means(AFCM) . Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased,and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means(FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM. | WANG Jing TANG Jilong LIU Jibin REN Chunying LIU Xiangnan FENG Jiang | 2009 | Chinese Geographical Science2009，19，1： | 1 |
| 5 | Image reconstruction for brain CT slices显示文摘Different modalities in biomedical images, like CT, MRI and PET scanners, provide detailed cross-sectional views of human anatomy. This paper introduces three-dimensional brain reconstruction based on CT slices. It contains filtering, fuzzy segmentation, matching method of contours, cell array structure and image animation. Experimental results have shown its validity. The innovation is matching method of contours and fuzzy segmentation algorithm of CT slices. | 吴建民 施鹏飞 | 2004 | Journal of Systems Engineering and Electronics2004，15，3： | 0 |
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