{"title":"人工神经网络在林业拟合问题中的应用","authors":"P. Radonja, M. Koprivica","doi":"10.1109/ICM.1998.825592","DOIUrl":null,"url":null,"abstract":"Neural networks with different architectures and different activation functions represent a powerful tool for solving many approximation problems. Combining the knowledge of a forestry theory with the empirical knowledge stored in an artificial neural networks (ANN) trained on examples, can bring very significant results with respect to traditional approaches. In our example neural networks represent a very powerful tool for solving problems of a fitting in forestry.","PeriodicalId":156747,"journal":{"name":"Proceedings of the Tenth International Conference on Microelectronics (Cat. No.98EX186)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial neural networks applications in problems of fitting in forestry\",\"authors\":\"P. Radonja, M. Koprivica\",\"doi\":\"10.1109/ICM.1998.825592\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Neural networks with different architectures and different activation functions represent a powerful tool for solving many approximation problems. Combining the knowledge of a forestry theory with the empirical knowledge stored in an artificial neural networks (ANN) trained on examples, can bring very significant results with respect to traditional approaches. In our example neural networks represent a very powerful tool for solving problems of a fitting in forestry.\",\"PeriodicalId\":156747,\"journal\":{\"name\":\"Proceedings of the Tenth International Conference on Microelectronics (Cat. No.98EX186)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Tenth International Conference on Microelectronics (Cat. No.98EX186)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICM.1998.825592\",\"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 Tenth International Conference on Microelectronics (Cat. No.98EX186)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICM.1998.825592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial neural networks applications in problems of fitting in forestry
Neural networks with different architectures and different activation functions represent a powerful tool for solving many approximation problems. Combining the knowledge of a forestry theory with the empirical knowledge stored in an artificial neural networks (ANN) trained on examples, can bring very significant results with respect to traditional approaches. In our example neural networks represent a very powerful tool for solving problems of a fitting in forestry.