{"id":217,"date":"2021-11-12T15:43:23","date_gmt":"2021-11-12T08:43:23","guid":{"rendered":"https:\/\/conf.icgbio.ru\/lyap100\/?page_id=217"},"modified":"2021-11-17T14:10:41","modified_gmt":"2021-11-17T07:10:41","slug":"072-thesis","status":"publish","type":"page","link":"https:\/\/conf.icgbio.ru\/lyap100\/en\/reports\/072-thesis\/","title":{"rendered":"072. Development of prediction for a multivariate dynamic systems control"},"content":{"rendered":"<p>The aim of this work is to develop an innovative, self-learning computer system for the combined multivariate analysis and prediction using circumstantial evidence and taking into account the phenomena that affect the studied parameters.<br \/>\nIn the developed system, the method of data analysis and forecasting based on genetic algorithm. System, in contrast to analogs can provide an economic assessment and forecast with greater accuracy. The basic building blocks of the program are the unit of statistical analysis, neural unit of analysis, the unit of genetic algorithm<\/p>\n<table class=\"t-data-grid grid-top-border\" style=\"width: 100%; height: 139px;\">\n<tbody>\n<tr class=\"line1\" style=\"height: 23px;\">\n<td class=\"report-label\" style=\"height: 23px;\">Abstracts file:<\/td>\n<td class=\"report-text\" style=\"height: 23px;\"><a href=\"https:\/\/conf.icgbio.ru\/lyap100\/wp-content\/uploads\/sites\/82\/2021\/11\/lyap100-072-\u0442\u0435\u0437\u0438\u0441\u044b.docx\" target=\"_blank\" rel=\"noopener\">\u0442\u0435\u0437\u0438\u0441\u044b.docx<\/a><\/td>\n<\/tr>\n<tr class=\"line2\" style=\"height: 70px;\">\n<td class=\"report-label\" style=\"height: 70px;\">Full text file:<\/td>\n<td class=\"report-text\" style=\"height: 70px;\"><a href=\"https:\/\/conf.icgbio.ru\/lyap100\/wp-content\/uploads\/sites\/82\/2021\/11\/lyap100-072-\u0420\u0410\u0417\u0420\u0410\u0411\u041e\u0422\u041a\u0410-\u041c\u041d\u041e\u0413\u041e\u0424\u0410\u041a\u0422\u041e\u0420\u041d\u041e\u0419-\u0421\u0418\u0421\u0422\u0415\u041c\u042b-\u041f\u0420\u041e\u0413\u041d\u041e\u0417\u0418\u0420\u041e\u0412\u0410\u041d\u0418\u042f-\u0414\u041b\u042f-\u0423\u041f\u0420\u0410\u0412\u041b\u0415\u041d\u0418\u042f-\u0414\u0418\u041d\u0410\u041c\u0418\u0427\u0415\u0421\u041a\u0418\u041c\u0418-\u0421\u0418\u0421\u0422\u0415\u041c\u0410\u041c\u0418.pdf\" target=\"_blank\" rel=\"noopener\">\u0420\u0410\u0417\u0420\u0410\u0411\u041e\u0422\u041a\u0410 \u041c\u041d\u041e\u0413\u041e\u0424\u0410\u041a\u0422\u041e\u0420\u041d\u041e\u0419 \u0421\u0418\u0421\u0422\u0415\u041c\u042b \u041f\u0420\u041e\u0413\u041d\u041e\u0417\u0418\u0420\u041e\u0412\u0410\u041d\u0418\u042f \u0414\u041b\u042f \u0423\u041f\u0420\u0410\u0412\u041b\u0415\u041d\u0418\u042f \u0414\u0418\u041d\u0410\u041c\u0418\u0427\u0415\u0421\u041a\u0418\u041c\u0418 \u0421\u0418\u0421\u0422\u0415\u041c\u0410\u041c\u0418.pdf<\/a><\/td>\n<\/tr>\n<tr class=\"line1\" style=\"height: 46px;\">\n<td class=\"report-label\" style=\"height: 46px;\">Presentation file:<\/td>\n<td class=\"report-text\" style=\"height: 46px;\"><a href=\"https:\/\/conf.icgbio.ru\/lyap100\/wp-content\/uploads\/sites\/82\/2021\/11\/lyap100-072-\u0418\u0432\u0430\u043d\u044e\u043a.ppt\" target=\"_blank\" rel=\"noopener\">\u0418\u0432\u0430\u043d\u044e\u043a.ppt<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>The aim of this work is to develop an innovative, self-learning computer system for the combined multivariate analysis and prediction using circumstantial evidence and taking into account the phenomena that affect the studied parameters. In the developed system, the method &hellip; <a href=\"https:\/\/conf.icgbio.ru\/lyap100\/en\/reports\/072-thesis\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":13,"featured_media":0,"parent":58,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/conf.icgbio.ru\/lyap100\/en\/wp-json\/wp\/v2\/pages\/217"}],"collection":[{"href":"https:\/\/conf.icgbio.ru\/lyap100\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/conf.icgbio.ru\/lyap100\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/conf.icgbio.ru\/lyap100\/en\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/conf.icgbio.ru\/lyap100\/en\/wp-json\/wp\/v2\/comments?post=217"}],"version-history":[{"count":3,"href":"https:\/\/conf.icgbio.ru\/lyap100\/en\/wp-json\/wp\/v2\/pages\/217\/revisions"}],"predecessor-version":[{"id":902,"href":"https:\/\/conf.icgbio.ru\/lyap100\/en\/wp-json\/wp\/v2\/pages\/217\/revisions\/902"}],"up":[{"embeddable":true,"href":"https:\/\/conf.icgbio.ru\/lyap100\/en\/wp-json\/wp\/v2\/pages\/58"}],"wp:attachment":[{"href":"https:\/\/conf.icgbio.ru\/lyap100\/en\/wp-json\/wp\/v2\/media?parent=217"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}