Development of an Efficient Prediction Model Based on a Nature-Inspired Technique for New Products: A Case of Industries From the Manufacturing Sector

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Author(s): Vikas Bhatnagar (NIT Warangal, India), Ritanjali Majhi (NIT Warangal, India)and S. L. Tulasi Devi (NIT Warangal, India)
Copyright: 2018
Pages: 23
Source title: Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms
Source Author(s)/Editor(s): Sujata Dash (North Orissa University, India), B.K. Tripathy (VIT University, India)and Atta ur Rahman (University of Dammam, Saudi Arabia)
DOI: 10.4018/978-1-5225-2857-9.ch009

Keywords: Artificial Intelligence / Biologically-Inspired Computing / Information Science Reference / Medicine & Healthcare

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Abstract

A lot of studies have been made on new product development process to make it an ideal procedure and many researchers have contributed significantly to achieve this by studying various factors associated with it. In this study, an attempt has been made to predict the optimal numbers of new products produced by electronics and metal & machinery industry by considering various factors those significantly affects the production pattern of these industries. For prediction purposes, functional linked artificial neural network (FLANN) with and without nature-inspired techniques have been used and comparison of performance for both the models have been done by using mean square error (MSE) and mean absolute percentage error (MAPE) as the measurement indices.

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Development of an Efficient Prediction Model Based on a Nature-Inspired Technique for New Products: A Case of Industries From the Manufacturing Sector

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