{"title":"兰花石斛的概率生长模型","authors":"Korakoch Kongsombut, R. Chaisricharoen","doi":"10.1109/APSIPA.2014.7041816","DOIUrl":null,"url":null,"abstract":"Dendrobium orchid has several plant states which are requiring different patterns of cultivation. In order to deliver appropriate advice to orchid farmers, status of their farms must be aware especially in the composite of orchid in each state. To model and predict farm status based on given initial data, a growth model is introduced in form of the CDF which can be easily adapted to estimate ratio of status change based on certain amount of plant in each state. The experiment involves around 120 orchid plants divided into four growing states with over one year of observations. The proposed model is confirmed with collected data which is strongly representing normal distribution behavior.","PeriodicalId":231382,"journal":{"name":"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Probabilistic growth model for dendrobium orchid\",\"authors\":\"Korakoch Kongsombut, R. Chaisricharoen\",\"doi\":\"10.1109/APSIPA.2014.7041816\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dendrobium orchid has several plant states which are requiring different patterns of cultivation. In order to deliver appropriate advice to orchid farmers, status of their farms must be aware especially in the composite of orchid in each state. To model and predict farm status based on given initial data, a growth model is introduced in form of the CDF which can be easily adapted to estimate ratio of status change based on certain amount of plant in each state. The experiment involves around 120 orchid plants divided into four growing states with over one year of observations. The proposed model is confirmed with collected data which is strongly representing normal distribution behavior.\",\"PeriodicalId\":231382,\"journal\":{\"name\":\"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APSIPA.2014.7041816\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIPA.2014.7041816","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dendrobium orchid has several plant states which are requiring different patterns of cultivation. In order to deliver appropriate advice to orchid farmers, status of their farms must be aware especially in the composite of orchid in each state. To model and predict farm status based on given initial data, a growth model is introduced in form of the CDF which can be easily adapted to estimate ratio of status change based on certain amount of plant in each state. The experiment involves around 120 orchid plants divided into four growing states with over one year of observations. The proposed model is confirmed with collected data which is strongly representing normal distribution behavior.