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Modelling fuel consumption in wheat production using artificial neural networks

Safa, Majeed; Samarasinghe, Sandhya - In: Energy 49 (2013) C, pp. 337-343

An ANN (artificial neural network) approach was used to model the fuel consumption of wheat production. This study was … conducted over 35,300 ha of irrigated and dry land wheat fields in Canterbury in the 2007–2008 harvest year. From an extensive … data collection involving 40 farms, the total fuel consumption in wheat production was estimated at 65.3 l/ha. On average …

Persistent link: https://www.econbiz.de/10011055226

An economic analysis of neural-based techniques applied for energy consumption prediction

Bǎlǎcian, Delia; Stancu, Stelian - In: Journal of Eastern Europe research in business & … 2023 (2023), pp. 1-12

Persistent link: https://www.econbiz.de/10014465647

Fuzzy-neural model with hybrid market indicators for stock forecasting

Adebiyi, A.A.; Ayo, C.K.; Otokiti, S.O. - In: International Journal of Electronic Finance 5 (2011) 3, pp. 286-297

A number of research had been carried out to forecast stock price based on technical indicators, which rely purely on historical stock price data. Nevertheless, their performance is not always satisfactory. In this paper, the effect of using hybrid market indicators of technical, fundamental...

Persistent link: https://www.econbiz.de/10009352618

A probabilistic neural network approach for modelling and classifying efficiency of GCC banks

Mostafa, Mohamed M. - In: International Journal of Business Performance Management 11 (2009) 3, pp. 236-258

of banks' relative efficiency due to their robustness and flexibility of modelling algorithms. The implications of these …

Persistent link: https://www.econbiz.de/10010669311

Chapter 9 Approximate Nonlinear Forecasting Methods

White, Halbert - 2006

We review key aspects of forecasting using nonlinear models. Because economic models are typically misspecified, the resulting forecasts provide only an approximation to the best possible forecast. Although it is in principle possible to obtain superior approximations to the optimal forecast...

Persistent link: https://www.econbiz.de/10014023697

Optimal Model Parameters of Inverse Kinematics Solution of a 3R Robotic Manipulator Using ANN Models

Karkalos, Nikolaos E.; Markopoulos, Angelos P.; Dossis, … - In: International Journal of Manufacturing, Materials, and … 7 (2017) 3, pp. 20-40

Solution of inverse kinematics equations of robotic manipulators constitutes usually a demanding problem, which is also required to be resolved in a time-efficient way to be appropriate for actual industrial applications. During the last few decades, soft computing models such as Artificial...

Persistent link: https://www.econbiz.de/10012046643

ANN‐GA based model for stock market surveillance

Punniyamoorthy, Murugesan; Joy Thoppan, Jose - In: Journal of Financial Crime 20 (2012) 1, pp. 52-66

Purpose – This paper attempts to develop a hybrid model using advanced data mining techniques for the detection of Stock Price Manipulation. The hybrid model detailed in this article elucidates the application of a Genetic Algorithm based Artificial Neural Network to classify stocks witnessing...

Persistent link: https://www.econbiz.de/10014865540

Forecasting of commercial energy consumption in India using Artificial Neural Network

Jebaraj, S.; Iniyan, S.; Kota, Hemanth - In: International Journal of Global Energy Issues 27 (2007) 3, pp. 276-301

The forecasting of energy consumption is essential for any country to study the future energy demand and to introduce the necessary government policies. This paper presents the formulation of forecasting models based on the Artificial Neural Network (ANN) for the consumption of conventional...

Persistent link: https://www.econbiz.de/10005751787

Forecasting of commercial energy consumption in India using Artificial Neural Network

Jebaraj, S.; Iniyan, S.; Kota, Hemanth - In: International Journal of Global Energy Issues 27 (2007) 3, pp. 276-301

Persistent link: https://www.econbiz.de/10008539277

Greek long-term energy consumption prediction using artificial neural networks

Ekonomou, L. - In: Energy 35 (2010) 2, pp. 512-517

In this paper artificial neural networks (ANN) are addressed in order the Greek long-term energy consumption to be predicted. The multilayer perceptron model (MLP) has been used for this purpose by testing several possible architectures in order to be selected the one with the best generalizing...

Persistent link: https://www.econbiz.de/10010809482