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Article
Publication date: 1 December 2021

Weige Yang, Yuqin Zhou, Wenhai Xu and Kunzhi Tang

The purposes are to explore corporate financial management optimization in the context of big data and provide a sustainable financial strategy for corporate development.

Abstract

Purpose

The purposes are to explore corporate financial management optimization in the context of big data and provide a sustainable financial strategy for corporate development.

Design/methodology/approach

First, the shortcomings of the traditional financial management model are analyzed under the background of big data analysis. The big data analytic technology is employed to extract financial big data information and establish an efficient corporate financial management model. Second, the deep learning (DL) algorithm is applied to implement a corporate financial early-warning model to predict the potential risks in corporate finance, considering the predictability of corporate financial risks. Finally, a corporate value-centered development strategy based on sustainable growth is proposed for long-term development.

Findings

The experimental results demonstrate that the financial early-warning model based on DL has an accuracy of 90.7 and 88.9% for the two-year financial alert, which is far superior to the prediction effect of the traditional financial risk prediction models.

Originality/value

The obtained results can provide a reference for establishing a sustainable development pattern of corporate financial management under the background of big data.

Details

Journal of Enterprise Information Management, vol. 35 no. 4/5
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 2 February 2024

He Du, Ming Yang, Songyan Wang and Tao Chao

This paper aims to investigate a novel impact time control guidance (ITCG) law based on the sliding mode control (SMC) for a nonmaneuvering target using the predicted interception…

Abstract

Purpose

This paper aims to investigate a novel impact time control guidance (ITCG) law based on the sliding mode control (SMC) for a nonmaneuvering target using the predicted interception point (PIP).

Design/methodology/approach

To intercept the target with the minimal miss distance and desired impact time, an estimation of time-to-go is introduced. This estimation results in a precise impact time for multimissiles salvo attack the target at the same time. Even for a large lead angle, the desired impact time is achieved by using the sliding mode and Lyapunov stability theory. The singularity issue of the proposed impact time guidance laws is also analyzed to achieve an arbitrary lead angle with the desired impact time.

Findings

Numerical scenarios with desired impact time are presented to illustrate the performance of the proposed ITCG law. Comparison with the state-of-art impact time guidance laws proves that the guidance law in this paper can enable the missile to intercept the target with minimal miss distance and final impact time error. This method enables multiple missiles to attack the target simultaneously with different distances and arbitrary lead angles.

Originality/value

An ITCG law based on sliding mode and Lyapunov stability theory is proposed, and the switching surface is designed based on a novel estimation time-to-go for the missile to intercept the target with minimal miss distance. To intercept the target with initial arbitrary lead angles and desired impact time, the authors analysis the singular issue in SMC to ensure that the missile can intercept the target with arbitrary lead angle. The proposed approach for a nonmaneuvering target using the PIP has simple forms, and therefore, they have the superiority of being implemented easily.

Details

Aircraft Engineering and Aerospace Technology, vol. 96 no. 2
Type: Research Article
ISSN: 1748-8842

Keywords

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