Search Results - subject:"Recurrent neural network"

Balluff, Stefan; Bendfeld, Jörg; Krauter, Stefan - In: International Journal of Grid and High Performance … 9 (2017) 1, pp. 61-74

Gathering knowledge not only of the current but also the upcoming wind speed is getting more and more important as the experience of operating and maintaining wind turbines is increasing. Not only with regards to operation and maintenance tasks such as gearbox and generator checks but moreover...

Persistent link: https://www.econbiz.de/10012045045

Evaluation of Recurrent Neural Network and its Variants for Intrusion Detection System (IDS)

Vinayakumar, R; Soman, K.P.; Poornachandran, Prabaharan - In: International Journal of Information System Modeling … 8 (2017) 3, pp. 43-63

This article describes how sequential data modeling is a relevant task in Cybersecurity. Sequences are attributed temporal characteristics either explicitly or implicitly. Recurrent neural networks (RNNs) are a subset of artificial neural networks (ANNs) which have appeared as a powerful,...

Persistent link: https://www.econbiz.de/10012045652

Hybrid modelling of an off line Arabic handwriting recognition system : results and evaluation

Meddeb, Ons; Maraoui, Mohsen; Aljawarneh, Shadi - In: International journal of intelligent enterprise : IJIE 4 (2017) 1/2, pp. 168-189

Persistent link: https://www.econbiz.de/10011858961

An Adaptive Second Order Neural Network with Genetic-Algorithm-based Training (ASONN-GA) to Forecast the Closing Prices of the Stock Market

Nayak, Sarat Chandra; Misra, Bijan Bihari; Behera, … - In: International Journal of Applied Metaheuristic … 7 (2016) 2, pp. 39-57

market. For comparative study of performance, two conventional neural based models such as a recurrent neural network (RNN …

Persistent link: https://www.econbiz.de/10012042929

Phased Method for Solving Multi-Objective MPM Job Shop Scheduling Problem

Tselios, Dimitrios C; Savvas, Ilias K.; Kechadi, M-Tahar - In: International Journal of Monitoring and Surveillance … 4 (2016) 1, pp. 42-61

The project portfolio scheduling problem has become very popular in recent years since many modern organizations operate in multi-project and multi-objective environment. Current project oriented organizations have to design a plan in order to execute a set of projects sharing common resources...

Persistent link: https://www.econbiz.de/10012046673

Deep learning in space and time for document image processing

Afzal, Muhammad Zeshan - 2016

Persistent link: https://www.econbiz.de/10011753911

Medium-term wind speeds forecasting utilizing hybrid models for three different sites in Xinjiang, China

Wang, Jianzhou; Qin, Shanshan; Zhou, Qingping; Jiang, Haiyan - In: Renewable Energy 76 (2015) C, pp. 91-101

recurrent neural network (ERNN) methods to construct the hybrid models named PMERNN and PAERNN. Then, this paper presents a …

Persistent link: https://www.econbiz.de/10011189865

Long-range prediction of retail sales using recurrent radial basis function neural network

Rout, Minakhi; Majhi, Babita - In: International journal of foresight and innovation … 10 (2015) 1, pp. 29-47

Persistent link: https://www.econbiz.de/10011524611

Application of echo state networks in short-term electric load forecasting

Deihimi, Ali; Showkati, Hemen - In: Energy 39 (2012) 1, pp. 327-340

. ESN as the state-of-the-art recurrent neural network (RNN) gains a reservoir of dynamics tapped by trained output units …

Persistent link: https://www.econbiz.de/10010808024

Generalized recurrent neural network for ϵ-insensitive support vector regression

Zhao, Yan; Liu, Qingshan - In: Mathematics and Computers in Simulation (MATCOM) 86 (2012) C, pp. 2-9

In this paper, a generalized recurrent neural network is proposed for solving ϵ-insensitive support vector regression … neural network with lower model complexity is designed for training the support vector machine. Furthermore, simulation … (ϵ-ISVR). The ϵ-ISVR is first formulated as a convex non-smooth programming problem, and then a generalize recurrent …

Persistent link: https://www.econbiz.de/10011051206