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Reconstructing positive surveys from negative surveys by improved artificial immune network

机译:通过改进的人工免疫网络从消极调查中重建积极调查

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Privacy protection in high efficiency and low energy consumption is a vital aspect in mobile and sensor networks. The negative survey acts as an advisable approach to sensitive data protection and individual privacy because negative survey can collect negative categories with high efficiency. To some extent, the conventional method is still less than satisfactory and leaves much to be desired in this aspect. Present methods for reconstructing positive survey and eliminating negative values (i.e. less than zero) may have problems such as rapid convergence or cannot achieving optimal values. In this paper, a novel method is proposed to reconstruct positive survey from negative survey. The proposed method based on artificial immune network can reconstruct preferable positive survey: more accuracy and no negative values. Experimental results show this method is conducive to the realization of more reasonable outcomes.
机译:高效,低能耗的隐私保护是移动和传感器网络的重要方面。否定调查可以作为敏感数据保护和个人隐私的明智方法,因为否定调查可以高效地收集否定类别。在某种程度上,常规方法仍然不能令人满意,并且在这方面有很多需要改进的地方。当前用于重建肯定调查并消除负值(即小于零)的方法可能会出现诸如快速收敛或无法获得最佳值的问题。本文提出了一种从消极调查重构积极调查的新方法。提出的基于人工免疫网络的方法可以重建较好的阳性调查:准确性更高,没有负值。实验结果表明,该方法有利于实现更合理的结果。

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