Enhancing Growth Curve Approach Using CGPANN for Predicting the Sustainability of New Food Products
作者： Jawad Ali , Gul Muhammad Khan , Sahibzada Ali Mahmud
DOI: 10.1007/978-3-662-44654-6_28
关键词: Growth curve (statistics) 、 Computer science 、 Sustainability 、 Artificial intelligence 、 Food products 、 Machine learning 、 New product development 、 Cartesian genetic programming
摘要: An enhancement to the growth curve approach based on neuro evolution is proposed develop various forecasting models investigate state and worth of producer, market a new product. The model obtained using newly introduced evolutionary called Cartesian Genetic Programming ANN (CGPANN). CGPANN helps in obtaining an optimum for all necessary parameters ANN. accurate computationally efficient obtained, achieving accuracy as high 93.37% time devised terrains, providing general mechanism mathematical agreement its application econometrics. Comparison with other contemporary evidences perfection thus vital power developing predicting sustainability products.
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