TY - JOUR AU - Li Chen, Anan Zhang, Chenxuan Wang, PY - 1970/01/01 Y2 - 2024/03/28 TI - Fa-Gasvm Evaluation on the Safety of Genetically Modified Organisms Causing People's Psychological Anxiety — Empirical Evidence from China JF - Forest Chemicals Review JA - JFCR VL - IS - SE - Articles DO - UR - http://forestchemicalsreview.com/index.php/JFCR/article/view/955 SP - 713-724 AB - At present, there are two views on the safety of gm technology. One holds that GM technology destroys the balance of the original nature and has unpredictable impacts on the ecological environment; the other holds that some foreseeable or potential hazards can be avoided by means of biosafety. In China, the public is most worried about the damage gm food will cause to human health. In the past decade, as the number of GM food has increased, more and more Chinese people have been troubled by GM food, and some of them have even experienced great psychological pressure. Under the influence of COVID-19, with the development of animal and plant genetic engineering in China, the role of genetically modified organisms is becoming more and more important. This paper analyzes the existence of the inverse system, identifies the initial inverse model by FA-GASVM, optimizes the parameters of the SVM by GA algorithm and generates the inverse model then, combines it with FA, and FA is introduced while the GASVM inverse is the main controller of the adaptive system. The forecasting results of FA-GASVM, FA-GASVM are compared, which indicates that FA-GASVM has more excellent performance than GASVM in forecasting biological safety of genetically modified. The study found, when the training set (test) sets is 19/20 base on GASVM, in the same training set and test set of the same, the biological safety of genetically modified quality evaluation of mean square error (MSE=0.9213, operation time was 129.528 S, the correlation coefficient is 96.0091%.FA-GASVM in the same training set and test set of the same, the mean square error (MSE = 0.8801, the running time of 123.399S,the correlation coefficient is 98.0725%. The FA-GASVM model is proved to be effective in optimizing parameters of SVM. Based on the proposed FA-GASVM, support vector machine parameters were optimized in this paper, which significantly improved the prediction accuracy of support vector machine in biosafety evaluation. At the same time, we need to use scientific thinking methods to guide the public to understand GM food; Educating the public about science; Building and maintaining trust among the public, government and scientists; Let the public freely choose genetically modified food, correctly guide people to genetically modified food health psychological treatment. ER -