BP Neural Network Based Valuation Of Biopharmaceutical Companies

With the rising number of aging population in the country and the increasing demand for health management,the development of the biopharmaceutical industry has ushered in an important opportunity.2021 saw the release of the National Outline of the 14 th Five-Year Plan and Vision 2035,which clearly proposed to strengthen the frontier research in science and technology in the field of biopharmaceuticals,in order to enhance the core position of the biopharmaceutical industry in strategic development.In order to improve the market share,competition within the biopharmaceutical industry is fierce,involving the listing of enterprises and various types of economic acts such as mergers and acquisitions,asset replacement and equity transfer between enterprises are becoming more and more frequent.A reasonable assessment of the value of biopharmaceutical enterprises is conducive to evaluating the commercial rationality of these economic acts,while enterprise value assessment also provides an effective value authentication tool for the construction of the biopharmaceutical industry to a certain extent.This paper investigates the prediction of biopharmaceutical enterprise value through BP neural network.After the applicability analysis,it is found that there are limitations in the traditional method for assessing enterprise value,so a new assessment method is introduced to evaluate the value of biopharmaceutical enterprises.This paper firstly establishes a system of evaluation indicators for biopharmaceutical enterprises,covering eight factors that have an impact on enterprise value,including profitability,growth,solvency,operational capability and innovation capability,and constructs a scientific BP neural network model.Shanghai Laishi was selected as a case study to predict its enterprise value at the valuation benchmark date,so as to explore the application of neural networks in expanding the enterprise value assessment method.The relative error of the neural network prediction for the case company was4.79%,and the error between the real value and the predicted value was small,proving that the BP neural network is feasible and effective for asset valuation.In fact,the entire process of neural network prediction relies on computer operation,avoiding human interference and ensuring objectivity in valuation;and the prerequisites for implementation are more relaxed,overcoming the limitations of most asset valuation methods,which is a significant advantage.In addition to enterprise valuation,neural networks are also useful for discovering the value of other types of assets.While the asset appraisal industry in China is still in its initial development stage,its improvement of the appraisal method system as a specialised value appraisal service will undoubtedly become the driving force of the industry’s development.BP neural networks have certain reference significance in the theoretical aspect of discovering new appraisal methods,and play a positive role in supporting the continuous development and innovation of the appraisal industry.