✦ LIBER ✦

Use of neural networks for predicting the performance of discontinuous gas-solid chilling machines

✍ Scribed by A. Palau; A. Delgado; E. Velo; L. Puigjaner

Publisher: Elsevier Science
Year: 1996
Tongue: English
Weight: 338 KB
Volume: 20
Category: Article
ISSN: 0098-1354
DOI: 10.1016/0098-1354(96)00060-9

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Performance of neural networks for predi

Performance of neural networks for predicting yarn properties using principal component analysis

✍ R. Chattopadhyay; Anirban Guha; Jayadeva 📂 Article 📅 2003 🏛 John Wiley and Sons 🌐 English ⚖ 77 KB 👁 2 views

Solid-liquid equilibrium of the GaInGa

Solid-liquid equilibrium of the GaInGaSb system and artificial neural network prediction

✍ Wu Wei; Yan Luming; Peng Ruiwu; Chen Nianyi; Zhang Jinwei 📂 Article 📅 1995 🏛 Elsevier Science 🌐 English ⚖ 298 KB

Use of input selection techniques to imp

Use of input selection techniques to improve the performance of an artificial neural network during the prediction of yarn quality properties

✍ Josphat Igadwa Mwasiagi; Xin Hou Wang; Xiu Bao Huang 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 361 KB 👁 2 views

A method for selecting similar learning

A method for selecting similar learning data in the prediction of time series using neural networks

✍ Hisashi Shimodaira 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 521 KB

Neural network prediction of thermophili

Neural network prediction of thermophilic (65°C) sulfidogenic fluidized-bed reactor performance for the treatment of metal-containing wastewater

✍ Erkan Sahinkaya; Bestamin Özkaya; Anna H. Kaksonen; Jaakko A. Puhakka 📂 Article 📅 2006 🏛 John Wiley and Sons 🌐 English ⚖ 164 KB 👁 1 views

## Abstract The performance of a fluidized‐bed reactor (FBR) based sulfate reducing bioprocess was predicted using artificial neural network (ANN). The FBR was operated at high (65°C) temperature and it was fed with iron (40–90 mg/L) and sulfate (1,000–1,500 mg/L) containing acidic (pH = 3.5–6) syn

Optimal artificial neural network archit

Optimal artificial neural network architecture selection for performance prediction of compact heat exchanger with the EBaLM-OTR technique

✍ Dumidu Wijayasekara; Milos Manic; Piyush Sabharwall; Vivek Utgikar 📂 Article 📅 2011 🏛 Elsevier Science 🌐 English ⚖ 841 KB

Artificial Neural Networks (ANN) have been used in the past to predict the performance of printed circuit heat exchangers (PCHE) with satisfactory accuracy. Typically published literature has focused on optimizing ANN using a training dataset to train the network and a testing dataset to evaluate it