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检索条件"主题词=artificial neural network modeling"
69 条 记 录,以下是1-10 订阅
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artificial neural network modeling of mechanical alloying process for synthesizing of metal matrix nanocomposite powders
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MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING 2007年 第1-2期466卷 274-283页
作者: Dashtbayazi, M. R. Shokuhfar, A. Simchi, A. KN Toosi Univ Technol Fac Mech Engn Tehran Iran Sharif Univ Technol Inst Nanosci & Nanotechnol Dept Mat Sci & Engn Tehran 14588 Iran
An artificial neural network model was developed for modeling of the effects of mechanical alloying parameters including milling time, milling speed and ball to powder weight ratio on the characteristics of Al-8 vol%S... 详细信息
来源: 评论
artificial neural network modeling to predict the plasma concentration of aminoglycosides in burn patients
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BIOMEDICINE & PHARMACOTHERAPY 2004年 第4期58卷 239-244页
作者: Yamamura, S Kawada, K Takehira, R Nishizawa, K Katayama, S Hirano, M Momose, Y Toho Univ Sch Pharmaceut Sci Chiba 2748510 Japan Nippon Med Coll Hosp Dept Pharm Serv Bunkyo Ku Tokyo 1138603 Japan
The goal was to use an artificial neural network model to predict the plasma concentration of aminoglycosides in burn patients and identify patients whose plasma antibiotic concentration would be sub-therapeutic based... 详细信息
来源: 评论
One-pot synthesis of novel 3D graphene/Fe3O4/agro-based waste material (Sesamum indicum) nanocomposite for wastewater treatment and artificial neural network modeling
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CHEMICAL ENGINEERING RESEARCH & DESIGN 2023年 第1期190卷 451-463页
作者: Nasiri, Ramin Zarei, Mahmoud Arsalani, Nasser Pezhhanfar, Sakha Someh, Abolfazl Ahmadi Panahian, Yasaman Univ Tabriz Fac Chem Dept Organ & Biochem Res Lab Polymer Tabriz *** Iran Univ Tabriz Fac Chem Dept Appl Chem Res Lab Environm Remediat Tabriz *** Iran Univ Tabriz Fac Chem Dept Analyt Chem Tabriz *** Iran
A One-Step hydrothermal process was applied in this study to synthesize magnetic Fe3O4/ 3D graphene/Sesamum indicum nanocomposite (M3DGSN). Acid Red 88 (AR88) was set at the target pollutant to be adsorbed and removed... 详细信息
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Analysis of diclofenac removal by metal-organic framework MIL-100(Fe) using multi-parameter experiments and artificial neural network modeling
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JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS 2021年 121卷 257-267页
作者: Jang, Ho-Young Kang, Jin-Kyu Lee, Seung-Chan Park, Jeong-Ann Kim, Song-Bae Seoul Natl Univ Dept Rural Syst Engn Environm Funct Mat & Water Treatment Lab Seoul South Korea Seoul Natl Univ Res Inst Agr & Life Sci Seoul South Korea Kangwon Natl Univ Dept Environm Engn Chunchon 24341 South Korea
The aim of study was to analyze diclofenac (DCF) removal from aqueous solutions by metal-organic framework MIL-100(Fe) using multi-parameter batch experiments and artificial neural network (ANN) modeling. First, singl... 详细信息
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Prediction of sugar yields during hydrolysis of lignocellulosic biomass using artificial neural network modeling
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BIORESOURCE TECHNOLOGY 2015年 188卷 128-135页
作者: Vani, Sankar Sukumaran, Rajeev Kumar Savithri, Sivaraman CSIR Natl Inst Interdisciplinary Sci & Technol Ctr Biofuels Div Biotechnol Trivandrum 695019 Kerala India CSIR Natl Inst Interdisciplinary Sci & Technol Proc Engn & Environm Technol Div Computat Modeling & Simulat Sect Trivandrum 695019 Kerala India
The present investigation was carried out to study application of ANN as a tool for predicting sugar yields of pretreated biomass during hydrolysis process at various time intervals. Since it is known that biomass loa... 详细信息
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artificial neural network modeling for the oxidation kinetics of divalent manganese ions during chlorination and the role of arsenite ions in the binary/ternary systems
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WATER RESEARCH 2024年 259卷 121876页
作者: Liao, Ziqiao Choi, Kungwon Ullah, Zahid Son, Moon Ahn, Yongtae Khan, Moonis Ali Prabhu, Subbaiah Muthu Jeon, Byong-Hun Hanyang Univ Dept Earth Resources & Environm Engn 222 Wangsimni Ro Seoul 04763 South Korea Korea Inst Sci & Technol Ctr Water Cycle Res 5 Hwarang Ro 14 gil Seoul 02792 South Korea Univ Sci & Technol KIST Sch Div Energy & Environm Technol Seoul 02792 South Korea Kyonggi Univ Dept Civil & Energy Syst Engn Suwon 16227 South Korea King Saud Univ Coll Sci Chem Dept Riyadh 11451 Saudi Arabia VIT AP Univ Sch Adv Sci Dept Chem Amaravati 522237 Andhra Pradesh India
This study investigated the coexistence and contamination of manganese (Mn(II)) and arsenite (As(III)) in groundwater and examined their oxidation behavior under different equilibrating parameters, including varying p... 详细信息
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Prediction of the thermal behavior of multi-walled carbon nanotubes-CuO-CeO2 (20-40-40)/water hybrid nanofluid using different types of regressors and evolutionary algorithms for designing the best artificial neural network modeling
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ALEXANDRIA ENGINEERING JOURNAL 2023年 84卷 184-203页
作者: Rostamzadeh-Renani, Reza Baghoolizadeh, Mohammadreza Sajadi, S. Mohammad Pirmoradian, Mostafa Rostamzadeh-Renani, Mohammad Baghaei, Sh. Salahshour, Soheil Energy Dept Politecn Milano Via Lambruschini 4 I-20156 Milan Italy Shahrekord Univ Dept Mech Engn Shahrekord *** Iran Cihan Univ Erbil Dept Nutr Erbil Kurdistan Regio Iraq Islamic Azad Univ Dept Mech Engn Khomeinishahr Branch Khomeinishahr Iran Istanbul Okan Univ Fac Engn & Nat Sci Dept Genet & Bioengn Istanbul Turkiye Bahcesehir Univ Fac Engn & Nat Sci Istanbul Turkiye Lebanese Amer Univ Dept Comp Sci & Math Beirut Lebanon
For conducting an analysis of the experimental data, it is imperative to establish a mathematical correlation between the input and output variables. This entails executing a curve fitting or regression procedure on t... 详细信息
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Prediction of aminoglycoside response against methicillin-resistant Staphylococcus aureus infection in burn patients by artificial neural network modeling
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BIOMEDICINE & PHARMACOTHERAPY 2008年 第1期62卷 53-58页
作者: Yamamura, Shigeo Kawada, Keiko Takehira, Rieko Nishizawa, Kenji Katayama, Shirou Hirano, Masaaki Momose, Yasunori Toho Univ Sch Pharmaceut Sci Chiba 2748510 Japan Nippon Med Coll Hosp Dept Pharm Serv Bunkyo Ku Tokyo 1138603 Japan
Objective: To predict the response of aminoglycoside antibiotics (arbekacin: ABK) against methicillin-resistant Staphylococcus aureus (MRSA) infection in burn patients after considering the severity of the burn injury... 详细信息
来源: 评论
Comment on "artificial neural network modeling of mechanical alloying process for synthesizing of metal matrix nanocomposite powders" by Dashtbayazi et al. [Mater. Sci. Eng. A 466 (2007) 274]
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MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING 2008年 第1-2期492卷 491-492页
作者: Sha, W. Queens Univ Belfast Sch Planning Architecture & Civil Engn Met Res Grp Belfast BT7 1NN Antrim North Ireland
来源: 评论
Informing the Work Zone Safety Policy Analysis: Reconciling Multivariate Prediction and artificial neural network modeling
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JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS 2024年 第2期150卷
作者: Shaer, Amin Talebian, Ahmadreza Mishra, Sabyasachee Isfahan Univ Technol Dept Transportat Engn Esfahan *** Iran Univ Memphis Dept Civil Engn 112D Engn Sci Bldg Memphis TN 38152 USA
Work zone safety, as an issue requiring complex solutions and tech-driven investment, has been a major concern for transportation agencies and policymakers. To help decision-makers prioritize investments, there is a n... 详细信息
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