Biblio

In recent years, with the continuous development of various new Internet technologies, big data, cloud computing and other technologies have been widely used in work and life. The further improvement of data scale and computing capability has promoted the breakthrough development of artificial intelligence technology. The generalization and classification of financial science and technology not only have a certain impact on the traditional financial business, but also put forward higher requirements for commercial banks to operate financial science and technology business. Artificial intelligence brings fresh experience to financial services and is conducive to increasing customer stickiness. Artificial intelligence technology helps the standardization, modeling and intelligence of banking business, and helps credit decision-making, risk early warning and supervision. This paper first discusses the influence of artificial intelligence on financial innovation, and on this basis puts forward measures for the innovation and development of bank financial science and technology. Finally, it discusses the problem of computer information security management in bank financial innovation in the era of artificial intelligence.

Cognitive acoustic (CA) is emerging as a promising technique for spectrum-efficient Underwater Acoustic Networks (UANs). Due to the unique features of UANs, especially the long propagation delay, the busy terminal problem and large interference range, traditional spectrum decision methods used for radio networks need an overhaul to work efficiently in underwater environment. In this paper, we propose a dynamic spectrum decision algorithm called Receiver-viewed Dynamic Borrowing (RvDB) algorithm for Underwater Cognitive Acoustic Networks (UCANs) to improve the efficiency of spectrum utilization. RvDB algorithm is with the following features. Firstly, the spectrum resource is decided by receiver. Secondly, the receivers can borrow the idle spectrum resource from neighbouring nodes dynamically. Finally, the spectrum sensing is completed by control packets on control channel which is separated from data channels. Simulation results show that RvDB algorithm can greatly improve the performance on spectrum efficiency.