Research On The Financial Distress Identification Of Listed Manufacturing Companies Based On K-Means Clustering

In the process of accelerating the new industrialization in China,while the manufacturing listed companies are grasping the development opportunities,they are prone to the decline of economic benefits and production and operation difficulties.The traditional financial dilemma identification focuses on the analysis of financial indicators,using ST and non-ST to indicate whether the enterprise is in financial distress.In this bipolar financial difficulties discrimination criteria,it is difficult to timely and effectively identify some manufacturing listed companies started into financial difficulties,also difficult to detail the degree of financial difficulties,some companies "pick hat ST" soon by "ST",difficult to real out from the financial difficulties,ST shen machine is manufacturing listed companies repeatedly by the typical representative of "ST".In this paper,the financial distress identification model of listed manufacturing enterprises is constructed,and ST Shen Ji is selected as a case study.First of all,first of all,read and sort out the research results about the identification of financial difficulties at home and abroad,and analyze the concepts and theories related to this topic.Secondly,based on theory and literature,for 2842-listed manufacturing companies in A-share market,traditional financial index data and non-financial index data are mined through data mining technology.Thirdly,K-Means clustering algorithm is used to extract regular data characteristics from these data,and then orderly clustering is carried out to form the financial dilemma classification standard,and establish the financial dilemma identification model for listed manufacturing companies.Further,this paper applies the financial dilemma model to analyze the case of ST Shen Ji repeatedly falling into financial dilemma.ST Shen Ji got into financial difficulties for the first time,the first time to get into financial difficulties again,analyzed its financial difficulties from various angles,and put forward suggestions for improvement.This paper draws the following conclusions:(1)the financial dilemma identification model of listed manufacturing companies based on k-means clustering can identify the financial difficulties of listed manufacturing companies more accurately and meticulously and apply them to specific case studies.(1)ST Shen machine first financial difficulties,did not really out of trouble.(3)Although the financial difficulties of ST Shenyang began to ease after restructuring,it still needs to accelerate the disposal of non-performing assets,improve the strength of product hardware and software,perfect the financial management mechanism,optimize product structure and other strong measures to truly get out of trouble and avoid the deepening of financial difficulties.In addition,according to the situation of listed companies in manufacturing industry,this paper puts forward some policy suggestions to strengthen industrial coordination and promoting the development and innovation of high-end industries,in order to provide ideas for scientific management of financial and operational difficulties in manufacturing industry and promote the healthy progress of the whole industry.