A Cost Control System for Internal Economic Management of Enterprises Based On Particle Swarm Optimization Algorithm (Informatica, 2024)
Sustainable development relies heavily on the efficient handling of financial information by small and medium-sized firms (SMEs), who are the engine that propels the global economy. In this research, we use the Particle Swarm Optimization (PSO) method as a foundation to build and optimize a financial information administration system for small and medium-sized enterprises (SMEs). The study started with an examination of the needs and difficulties associated with financial information management for SMEs. After that, we dive into the building process of a B/S structure-based SME financial management system and provide a PSO-based early detection model of a SME financial crisis, highlighting the algorithm's possible usefulness in this field. We demonstrate the efficacy of the PSO algorithm in forecasting company financial risk and the trajectory of stock prices in the same time via simulation and experimental verification. Using the algorithm helps businesses better handle market instability and competitive pressure while also improving the effectiveness of financial information administration and reducing the danger of human mistake. Businesses' adaptability and competitiveness may be boosted by this system's ability to determine solutions to their unique requirements.