{"title":"基于大豆叶片颜色的ANFIS法鉴定大豆叶片中营养氮","authors":"Rahmawati Febrifyaning Tias","doi":"10.54732/jeecs.v1i2.173","DOIUrl":null,"url":null,"abstract":"The social demand for soybeans increas continously along with the growth of population. Increasing production of soybeans has many obstacles, among others attacked a variety of pests, diseases and nutrient deficiencies. In this research discusses the nutrients nitrogen deficiency symptoms based on soybean leaf colour. An Agricultural expert is needed to determine its cause. However, limited number of Agricultural Experts can not solve the Farmers problem at the same time. Therefore, systems are needed for early identification accurately of nutrient nitrogen in soybean leaves. In this research uses “ Adaptive Neuro-Fuzzy Inference System (ANFIS) Methode” which is expected success rate of 80%.","PeriodicalId":273708,"journal":{"name":"JEECS (Journal of Electrical Engineering and Computer Sciences)","volume":"373 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification of Nutrient Nitrogen in the Leaves of Soybean Plants Using ANFIS Based On Soybean Leave Colour\",\"authors\":\"Rahmawati Febrifyaning Tias\",\"doi\":\"10.54732/jeecs.v1i2.173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The social demand for soybeans increas continously along with the growth of population. Increasing production of soybeans has many obstacles, among others attacked a variety of pests, diseases and nutrient deficiencies. In this research discusses the nutrients nitrogen deficiency symptoms based on soybean leaf colour. An Agricultural expert is needed to determine its cause. However, limited number of Agricultural Experts can not solve the Farmers problem at the same time. Therefore, systems are needed for early identification accurately of nutrient nitrogen in soybean leaves. In this research uses “ Adaptive Neuro-Fuzzy Inference System (ANFIS) Methode” which is expected success rate of 80%.\",\"PeriodicalId\":273708,\"journal\":{\"name\":\"JEECS (Journal of Electrical Engineering and Computer Sciences)\",\"volume\":\"373 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JEECS (Journal of Electrical Engineering and Computer Sciences)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54732/jeecs.v1i2.173\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JEECS (Journal of Electrical Engineering and Computer Sciences)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54732/jeecs.v1i2.173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification of Nutrient Nitrogen in the Leaves of Soybean Plants Using ANFIS Based On Soybean Leave Colour
The social demand for soybeans increas continously along with the growth of population. Increasing production of soybeans has many obstacles, among others attacked a variety of pests, diseases and nutrient deficiencies. In this research discusses the nutrients nitrogen deficiency symptoms based on soybean leaf colour. An Agricultural expert is needed to determine its cause. However, limited number of Agricultural Experts can not solve the Farmers problem at the same time. Therefore, systems are needed for early identification accurately of nutrient nitrogen in soybean leaves. In this research uses “ Adaptive Neuro-Fuzzy Inference System (ANFIS) Methode” which is expected success rate of 80%.