Abstract : An enhancement to the growth curve approach based on neuro evolution is proposed to develop various forecasting models to investigate the state and worth of the producer, to market a new product. The forecasting model is obtained using a newly introduced neuro evolutionary approach called Cartesian Genetic Programming based ANN (CGPANN). CGPANN helps in obtaining an optimum model for all the necessary parameters of an ANN. An accurate and computationally efficient model is obtained, achieving an accuracy as high as 93.37% on the time devised terrains, providing a general mechanism for forecasting models in mathematical agreement to its application in econometrics. Comparison with other contemporary model evidences the perfection of the proposed model thus its vital power in developing the growth curve approach for predicting the sustainability of new products.
Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.286-297, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_28〉
https://hal.inria.fr/hal-01391325
Contributeur : Hal Ifip
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Dernière modification le : vendredi 1 décembre 2017 - 01:16:36
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Jawad Ali, Gul Khan, Sahibzada Mahmud. Enhancing Growth Curve Approach Using CGPANN for Predicting the Sustainability of New Food Products. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.286-297, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_28〉. 〈hal-01391325〉
