面向可解释性人工智能与大数据的模糊系统发展展望

Development prospect of fuzzy system oriented to interpretable artificial intelligence and big data

模糊系统作为一种万能逼近器具有很强的可解释性,已被广泛应用在各个领域。尽管目前模糊系统的理论研究不够成熟,仍然存在诸如规则太多、优化困难、维度诅咒等问题,难以处理高维大数据。尽管深度神经网络取得了突出进展,能很好处理图像和语音等大数据,但其可解释性不好,难以用于安全相关的重要场合。因此,非常有必要研究一种基于模糊系统的可解释性强的人工智能算法。结合深度神经网络和模糊系统两者的优点,研究深度模糊系统及其算法,将有可能解决高维大数据问题。主要对模糊系统的发展历程与研究进展分别进行详细阐述,并根据其现有的问题指出其未来的发展方向,对进一步的研究问题进行展望。

As a universal approximator with strong interpretability,fuzzy system has been widely used in various fields.Although the current theoretical research on fuzzy system is not mature enough,there are still many problems such as too many rules,optimization difficulties,dimension curse,which make it difficult to deal with high-dimensional large data.Although deep neural network has made remarkable progress and can process large data such as image and voice very well,its interpretability is not good and it is difficult to be used in important security-related occasions.Therefore,it is necessary to study an interpretable artificial intelligence algorithm based on fuzzy system.Combining the advantages of deep neural network and fuzzy system,it is possible to solve the problem of high dimensional and large data by studying the deep fuzzy system and its algorithm.The development history and research progress of fuzzy system separately was mainly reviews,and its future development direction according to its existing problems was pointed out,and the summary of this article and the prospect for further research about the problems were given.