Universal approximation using radial-basis-function networks
Neural Computation
Neural and Adaptive Systems: Fundamentals through Simulations with CD-ROM
Neural and Adaptive Systems: Fundamentals through Simulations with CD-ROM
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Clustering Moving Data With a Modified Immune Algorithm
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
Exploiting the Analogy between the Immune System and Sparse Distributed Memories
Genetic Programming and Evolvable Machines
A New Look at Nonlinear Time Series Prediction with NARX Recurrent Neural Network
SBRN '06 Proceedings of the Ninth Brazilian Symposium on Neural Networks
Applying knowledge engineering techniques to customer analysis in the service industry
Advanced Engineering Informatics
An in-process customer utility prediction system for product conceptualisation
Expert Systems with Applications: An International Journal
Soft computing in engineering design - A review
Advanced Engineering Informatics
Human-centric product conceptualization using a design space framework
Advanced Engineering Informatics
Advances in artificial immune systems
IEEE Computational Intelligence Magazine
A quality-time-cost-oriented strategy for product conceptualization
Advanced Engineering Informatics
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The twenty-first century is marked by fast evolution of customer tastes and needs. Research has shown that customer requirements could vary in the temporal space between product conceptualization and market introduction. In such cases, the products generated might not fit the consumer needs as companies originally expected. This paper advocates the proactive management and forecast of the dynamic customer requirements in bid to lower the inherent risk in developing products for fast shifting markets. The research identified the principles of artificial immune and neural systems as a solution to the problem. A customer requirements analysis and forecast (CRAF) system is defined in this paper to address the issue. The system aims to support product development functions with quantitative and qualitative customer requirements information, in the pursuit of generating products for near future markets. A case study is presented in this article to illustrate the functions of the system.