✦ LIBER ✦

Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances

✍ Scribed by Khosravi, A.; Nahavandi, S.; Creighton, D.; Atiya, A.F.

Book ID: 119942504
Publisher: IEEE
Year: 2011
Tongue: English
Weight: 774 KB
Volume: 22
Category: Article
ISSN: 1045-9227
DOI: 10.1109/TNN.2011.2162110

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

A neural network-GARCH-based method for

A neural network-GARCH-based method for construction of Prediction Intervals

✍ Khosravi, Abbas; Nahavandi, Saeid; Creighton, Doug 📂 Article 📅 2013 🏛 Elsevier Science 🌐 English ⚖ 732 KB

Particle swarm optimization for construc

Particle swarm optimization for construction of neural network-based prediction intervals

✍ Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas 📂 Article 📅 2014 🏛 Elsevier Science 🌐 English ⚖ 658 KB

A prediction interval-based approach to

A prediction interval-based approach to determine optimal structures of neural network metamodels

✍ Abbas Khosravi; Saeid Nahavandi; Doug Creighton 📂 Article 📅 2010 🏛 Elsevier Science 🌐 English ⚖ 571 KB

Recent advances of neural network-based

Recent advances of neural network-based EM-CAD

✍ Humayun Kabir; Ming Yu; Q. J. Zhang 📂 Article 📅 2010 🏛 John Wiley and Sons 🌐 English ⚖ 561 KB

In this article, we provide an overview of recent advances in computer-aided design techniques using neural networks for electromagnetic (EM) modeling and design applications. Summary of various recent neural network modeling techniques including passive component modeling, design and optimization u

Prediction models in the design of neura

Prediction models in the design of neural network based ECG classifiers: A neural network and genetic programming approach

✍ Chris D Nugent; Jesus A Lopez; Ann E Smith; Norman D Black 📂 Article 📅 2002 🏛 BioMed Central 🌐 English ⚖ 281 KB

Pattern recognition and prediction study

Pattern recognition and prediction study of rock burst based on neural network

✍ Hong Li 📂 Article 📅 2010 🏛 China Coal Society 🌐 English ⚖ 416 KB