GDL

Journal from gdlhub / 2020-04-07 11:39:48
Oleh : Vikas Bhatnagar, Ritanjali Majhi, Sunil Sahadev, King Saud University
Dibuat : 2020-02-10, dengan 1 file

Keyword : Cascaded artificial neural network, Multiple linear regression, New product launch, Functional linked artificial neural network, Particle swarm optimization
Url : http://www.sciencedirect.com/science/article/pii/S1319157817301817
Sumber pengambilan dokumen : Web

Predicting numbers of new products to be launched by the firms in a particular time period is considered as the most mystified and strategically important decision. Importance of this aspect could be realized by looking at the low success rate of new products in the market. Identifying numbers of new products potentially accepted by the market may reduce the investment and scant resources consumption by firms. In this study, statistical multiple linear regression, and artificial neural network techniques modeled as simple and cascaded networks combined with nature inspired algorithm have been implemented. Artificial neural network has shown significant performance results and further cascading helps in enhancing the prediction accuracy along with better convergence capability of the developed models for the predicament.

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