利用农福信息系统和确定性模型预测趋势专题 (Prediction of trending topics using ANFIS and deterministic models)

Trending topics are often the result of the spreading of information between users of social networks. These special topics can be regarded as rumors. The spreading of a rumor is often studied with the same techniques as in epidemics spreading. It is common that many datasets may not have enough measured variables, so we propose a method for studying the general behavior of the spreaders by selecting estimated variables given by the deterministic model. In order to provide a good approximation, we implemented an adaptative neuro fuzzy inference system (ANFIS). So, in our numerical experimentations, a deterministic approach using SIR and SIRS models (with delay) for two different topics is used. Thus, the authors just applied the ANFIS model for their application and the deterministic model as the preprocessing input variable.

翻译：社交网络用户之间传播信息的结果往往是趋势论题。这些特殊论题可被视为流言。传闻的传播往往以与流行病传播相同的技术来研究。许多数据集可能没有足够的测量变量,因此我们提出一种方法,通过选择确定模型给出的估计变量来研究传播者的一般行为。为了提供良好的近似,我们实施了适应性神经模糊推断系统(ANFIS ) 。因此,在数字实验中,对两个不同专题采用了使用SIR和SIRS模型的确定性方法(延缓),因此,作者只是应用ANFIS模型来应用这些模型,而确定模型作为预处理输入变量。