Artificial neural networks for supporting production planning and control

Corsten, Hans; May, Constantin

doi:10.1016/0166-4972(95)00024-0

Cited by 6 publications

(8 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After that, the same authors (Kuo & Xue, 1998b) expand the existing FNN model with fuzzy IF-THEN rules for pater recognition in prediction. Considering different internal and external factors, many other authors use NN for forecasting sales process in order to better plan capacity, production and other activities (Luxhøj, (Corstena & May, 1996) and (Feng, Li, Cen & Huang, 2003) point out the possibility of using NN for managing the production process. When it comes to the production planning (Cavalieri,Maccarrone & Pinto, 2004), for modelling cause and effect relation between design solutions and costs, traditional statistical model and NN are combined.…”

Section: Neural Networkmentioning

confidence: 99%

“…Feedforward & back propag. learning algorithm & multiple layers, (Bansal et all., 1994), (Dutta et all., 1994), (Hill & Remus, 1994), (Corstena & May, 1996), (Agrawal & Schorling, 1996), (Ansuj et all., 1996), (Kuo & Xue, 1998a), (Kuo & Xue, 1998b), (Walczak, 2001), (Kuo, 2001), (Zhang et all., 2001), (Chiang et all., 2001), (Calderon & Cheh, 2002), (Feng et all., 2003), (Cavalieri et all., 2004), (Zhang & Qi, 2005), (Co, 2007), (Aburto & Weber, 2007)…”

Section: Neural Networkmentioning

confidence: 99%

“…Table 3 indicates a significant usage of both evaluation and estimation methods for fuzzy logic, and in case of neural networks, forecasting method is mostly applied. From a total of 73 analysed papers, the largest number is published in the journal Fuzzy Sets and Systems (15), in the Applied Soft Computing (6) and Decision Support Systems (6) and Expert Systems with Applications (5) journals. The variety of journals in which papers were published indicate that the application of SCT in the field of business process management has been recognized by the wider professional community.…”

Section: Nn and Flmentioning

confidence: 99%

“…The variety of journals in which papers were published indicate that the application of SCT in the field of business process management has been recognized by the wider professional community. (Hill & Remus, 1994), (Corstena & May, 1996), (Chiang et all., 2001), (Volkner & Werners, 2002), (Jamshidi, 2003), (Feng et all., 2003), (Cheng, 2005), (Co, 2007), (Parchami & Mashinchi, 2007), (Wu, 2009), (Faraz & Shapiro, 2010), (Torabi et all., 2010), (Zobel & Cook 2011), (Kao & Liu, 2011), (Kaya & Kahraman, 2011), (Kar et all., 2014), (Huang et all., 2015), (Martinez & Selles, 2015).…”

Section: Nn and Flmentioning

confidence: 99%

See 3 more Smart Citations

Managing business processes using soft computing techniques – a literature review

Vojtek

2017

Manage: J. Sustainable Bus. Manage, Solutions Emerging Econ.

View full text Add to dashboard Cite

Non-ideal and turbulent environment is affecting the business operations of today's companies. The influence and behavior of external factors is not possible or very difficult to predict, but necessary to consider in the decision making process at all organizational levels. Development of computer technologies allowed companies processing large amounts of data in order to make decisions which take into account both internal and external factors. Due to their tolerance of imprecision and uncertainty, Soft computing techniques (SCT) are increasingly used in solving those problems. They are characterized by the ability to adapt quickly to the changes in the environment, stability when processing large amounts of inaccurate data and real time responsiveness. The basic and most commonly used Soft Computing techniques are Fuzzy logic (FL) and neural networks (NN). This paper gives a review of 78 papers referring to the development of theory and practical application of soft computing techniques in business process management. Papers were selected based on the journals impact factor and year of publication (with the focus on recent papers). Approximately, equal number of both Fuzzy logic and Neural Network techniques was tried to be captured. Although this review is not final, it can be considered as a valid guide to explore the opportunities and possibilities which fuzzy logic and neural networks offer process owners in managing their business processes. In conclusion of this paper, fields for further research have been identified.

show abstract

Section: Neural Networkmentioning

confidence: 99%

Section: Neural Networkmentioning

confidence: 99%

Section: Nn and Flmentioning

confidence: 99%

Section: Nn and Flmentioning

confidence: 99%

See 2 more Smart Citations

Managing business processes using soft computing techniques – a literature review

Vojtek

2017

Manage: J. Sustainable Bus. Manage, Solutions Emerging Econ.

View full text Add to dashboard Cite

show abstract

“…The main advantages of ANNs are the ability to self-organize, the ability to learn the ability to generalize, and the fault tolerance (Fausett 1994;Corsten and May 1996). On the other hand, the main disadvantage is the lack of self-explanation (i.e., the solution procedure loses transparency resulting in problems of acceptability).…”

Section: The Artificial Neural Network Technologymentioning

confidence: 99%

Neural networks in production scheduling: Intelligent solutions and future promises

Metaxiotis

2003

Applied Artificial Intelligence

View full text Add to dashboard Cite

The way their neurons are connected. * The specific kinds of computations their neurons do. * The way they transmit patterns of activity throughout the network. * The way they learn, including their learning rate.With regard to the arrangement of the neurons, we distinguish between layered and unlayered networks. In layered networks, the neurons are grouped in layers. Between the input and the output layer, which has external connections only, there are one or more hidden layers. The input data are transmitted from the input layer via the hidden layers to the output layer. The signal flow in layered networks is forward directed (feedforward 362K. Metaxiotis and J. Psarras Downloaded by [UQ Library]

show abstract

Microstructure‐ and Theory‐Based Modeling and Simulation of Batteries and Fuel Cells

Latz

Danner

Horstmann

et al. 2019

Chemie Ingenieur Technik

View full text Add to dashboard Cite

The quality of digitalized design and development processes for advanced electrochemical technologies depends crucially on the accuracy of available models and the level of details at which simulations can be performed. In this article, an overview is given over recent advances in developing coupled models of transport and electrochemistry and simulation tools to investigate and modify very detailed processes in batteries and fuel cells, two of the decisive electrochemical technologies for future energy markets.

show abstract

Artificial neural networks for supporting production planning and control

Cited by 6 publications

References 22 publications

Managing business processes using soft computing techniques – a literature review

Managing business processes using soft computing techniques – a literature review

Neural networks in production scheduling: Intelligent solutions and future promises

Microstructure‐ and Theory‐Based Modeling and Simulation of Batteries and Fuel Cells

Contact Info

Product

Resources

About