Intelligent algorithm-based analysis of corporate financial decisions in the era of cloud accounting

Abstract

Abstract The development of cloud computing technology has promoted a new information technology revolution, and the arrival of the cloud accounting era has brought new ideas to enterprise financial decision-making. This paper first introduces the improved swarm intelligence algorithm grasshopper optimization algorithm optimization, using reverse learning the Levy flight mechanism to improve the global search ability of the original grasshopper algorithm, using the Gaussian variation mechanism to increase the diversity of the population to achieve algorithm optimization. The IGOA algorithm is then used to optimize the internal parameters of KELM by dynamically adjusting the optimal parameters based on the training set data through a 5-fold cross-validation analysis to evaluate the external classification performance. Then the factors affecting the financial decision analysis and the financial decision process in the cloud accounting era are introduced, and finally, some problems in traditional enterprise decision methods and the impact of intelligent algorithms on enterprise financial decisions are analyzed. In terms of the existing problems, the main ones are: 83% of them think that the traditional enterprise decision-making methods need to be innovated, and 83% of them think there is a shortage of professionals with professional financial decision-making expertise. On the impact of intelligent algorithms on enterprise financial decision-making, 88% think that the decision analysis dimension has been broadened based on intelligent algorithms, and 85% think that the decision risk has achieved fine control. The development and application of intelligent algorithms and cloud accounting technology have an important and positive effect on the financial decision-making mode of enterprises.