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Alternative approaches to the prediction of electricity prices
Domanski, Pawel D.; Gintrowski, Mateusz - In: International journal of energy sector management : IJESM 11 (2017) 1, pp. 3-27
Persistent link: https://www.econbiz.de/10011704812
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Alternative approaches to the prediction of electricity prices
Domanski, Pawel D.; Gintrowski, Mateusz - In: International Journal of Energy Sector Management 11 (2017) 1, pp. 3-27
the field of the electricity price forecasting. Thus, it gives a new impact for further research enabling development of …
Persistent link: https://www.econbiz.de/10014773862
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Composite forecasting approach, application for next-day electricity price forecasting
Mirakyan, Atom; Meyer-Renschhausen, Martin; Koch, Andreas - In: Energy economics 66 (2017), pp. 228-237
Persistent link: https://www.econbiz.de/10011896468
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Neural Networks in Marketing: Modelling Consumer Responses to Advertising Stimuli
Curry, Bruce; Moutinho, Luiz - In: European Journal of Marketing 27 (1993) 7, pp. 5-20
Examines the theoretical base of the neural network technique showing, for example, that it is linked in formal and practical terms with expert systems and that it uses a statistical approach. After beginning with a discussion of models of information processing by consumers, proceeds to outline...
Persistent link: https://www.econbiz.de/10014723051
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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...
Persistent link: https://www.econbiz.de/10011055226
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Intelligent approach to determining optimal burn‐in time and cost for electronic products
Su, Chao‐Ton; Wu, Cheng‐Lin - In: International Journal of Quality & Reliability Management 18 (2001) 5, pp. 549-559
attempted to determine the optimum burn‐in time and cost for a device or a system. However, for the mathematical model, many … assumptions are inappropriate due to practical concerns, and for the cost model, the required costs are difficult to find. How to … effectively determine the optimal burn‐in time and cost has perplexed manufacturers for quite some time. In the actual …
Persistent link: https://www.econbiz.de/10014800095
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Modelling and evaluating service quality measurement using neural networks
Behara, Ravi S.; Fisher, Warren W.; Lemmink, Jos G.A.M. - In: International Journal of Operations & Production Management 22 (2002) 10, pp. 1162-1185
Effective measurement and analysis of service quality are an essential first step in its improvement. This paper discusses the development of neural network models for this purpose. A valid neural network model for service quality is initially developed. Customer data from a SERVQUAL survey at...
Persistent link: https://www.econbiz.de/10014789598
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Forecasting tourism demand by fuzzy time series models
Huarng, Kun‐Huang; Hui‐Kuang Yu, Tiffany; Moutinho, Luiz - In: International Journal of Culture, Tourism and … 6 (2012) 4, pp. 377-388
forecasting. Design/methodology/approach – Fuzzy sets are for modeling imprecise data and neural networks are for establishing non …‐linear relationships among fuzzy sets. A neural network based fuzzy time series model is adapted as the forecasting model. Both in …‐sample estimation and out‐of‐sample forecasting are performed. Findings – This study outperforms previous studies undertaken during the …
Persistent link: https://www.econbiz.de/10014768346
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Selection of optimal parameters in gas‐assisted injection moulding using a neural network model and the Taguchi method
Chiu, Chih‐Chou; Su, Chao‐Ton; Yang, Gong‐Shung; … - In: International Journal of Quality Science 2 (1997) 2, pp. 106-120
identify what provides the best forecasting of performance measure. In addition, to verify the generalization capability of the …
Persistent link: https://www.econbiz.de/10014802387
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A study of using artificial neural networks to develop an early warning predictor for credit union financial distress with comparison to the probit model
Tan, Clarence N.W.; Dihardjo, Herlina - In: Managerial Finance 27 (2001) 4, pp. 56-77
Outlines previous research on company failure prediction and discusses some of the methodological issues involved. Extends an earlier study (Tan 1997) using artificial neural networks (ANN) to predict financial distress in Australian credit unions by extending the forecast period of the models,...
Persistent link: https://www.econbiz.de/10014939551