{"title":"RSM和ANN模型对水杨花种子活性炭吸附处理结晶紫染料模拟废水的预测能力评价","authors":"C. C. Okoye, O. Onukwuli, C. F. Okey-Onyesolu","doi":"10.1080/22243682.2018.1497534","DOIUrl":null,"url":null,"abstract":"A comparative evaluation of the predictive capability of response surface methodology (RSM) and artificial neural network (ANN) in adsorptive treatment of dye simulated wastewater using acid activa...","PeriodicalId":17291,"journal":{"name":"Journal of the Chinese Advanced Materials Society","volume":"31 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Predictive capability evaluation of RSM and ANN models in adsorptive treatment of crystal violet dye simulated wastewater using activated carbon prepared from Raphia hookeri seeds\",\"authors\":\"C. C. Okoye, O. Onukwuli, C. F. Okey-Onyesolu\",\"doi\":\"10.1080/22243682.2018.1497534\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A comparative evaluation of the predictive capability of response surface methodology (RSM) and artificial neural network (ANN) in adsorptive treatment of dye simulated wastewater using acid activa...\",\"PeriodicalId\":17291,\"journal\":{\"name\":\"Journal of the Chinese Advanced Materials Society\",\"volume\":\"31 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Chinese Advanced Materials Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/22243682.2018.1497534\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Chinese Advanced Materials Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/22243682.2018.1497534","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predictive capability evaluation of RSM and ANN models in adsorptive treatment of crystal violet dye simulated wastewater using activated carbon prepared from Raphia hookeri seeds
A comparative evaluation of the predictive capability of response surface methodology (RSM) and artificial neural network (ANN) in adsorptive treatment of dye simulated wastewater using acid activa...
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
