{"title":"人口生活水平的神经进化预测","authors":"L. Bilgaeva, E. Sadykova, V. Filippov","doi":"10.2991/ahcs.k.191206.004","DOIUrl":null,"url":null,"abstract":"The article is devoted to the problem of forecasting indicators of living standards using neuroevolutionary approach. The NEAT method is considered that allows generating the neural network topology automatically. The paper proposes modification of this method and its implementation based on the activation functions mutation, which enabled to expand the set of possible solutions. A comparative analysis of the training, testing, and forecasting accuracy is carried out. Target indicator forecasting was performed with preliminary forecasting of factor signs that increased forecasting accuracy in comparison to the Windows method used to forecast target indicators directly.","PeriodicalId":287734,"journal":{"name":"Proceedings of the Fourth Workshop on Computer Modelling in Decision Making (CMDM 2019)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Neuroevolution Forecasting of the Living Standards of the Population\",\"authors\":\"L. Bilgaeva, E. Sadykova, V. Filippov\",\"doi\":\"10.2991/ahcs.k.191206.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article is devoted to the problem of forecasting indicators of living standards using neuroevolutionary approach. The NEAT method is considered that allows generating the neural network topology automatically. The paper proposes modification of this method and its implementation based on the activation functions mutation, which enabled to expand the set of possible solutions. A comparative analysis of the training, testing, and forecasting accuracy is carried out. Target indicator forecasting was performed with preliminary forecasting of factor signs that increased forecasting accuracy in comparison to the Windows method used to forecast target indicators directly.\",\"PeriodicalId\":287734,\"journal\":{\"name\":\"Proceedings of the Fourth Workshop on Computer Modelling in Decision Making (CMDM 2019)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fourth Workshop on Computer Modelling in Decision Making (CMDM 2019)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/ahcs.k.191206.004\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fourth Workshop on Computer Modelling in Decision Making (CMDM 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/ahcs.k.191206.004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neuroevolution Forecasting of the Living Standards of the Population
The article is devoted to the problem of forecasting indicators of living standards using neuroevolutionary approach. The NEAT method is considered that allows generating the neural network topology automatically. The paper proposes modification of this method and its implementation based on the activation functions mutation, which enabled to expand the set of possible solutions. A comparative analysis of the training, testing, and forecasting accuracy is carried out. Target indicator forecasting was performed with preliminary forecasting of factor signs that increased forecasting accuracy in comparison to the Windows method used to forecast target indicators directly.