Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Developing Online Games: An Insider's Guide
Developing Online Games: An Insider's Guide
Group decision making to better respond customer needs in software development
Computers and Industrial Engineering
Prony residual analysis for the identification of cardiac arrhythmias
ICASSP '95 Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Consumer behavior in online game communities: A motivational factor perspective
Computers in Human Behavior
Fuzzy-genetic algorithm for automatic fault detection in HVAC systems
Applied Soft Computing
Prediction of chaotic time series based on the recurrent predictor neural network
IEEE Transactions on Signal Processing
Playing to learn: case-injected genetic algorithms for learning to play computer games
IEEE Transactions on Evolutionary Computation
E-business in the entertainment sector: the Egmont case
International Journal of Information Management: The Journal for Information Professionals
Reproducing chaos by variable structure recurrent neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
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Because of the huge potential profit, the development of virtual items in massive multiplayer online role playing games (MMORPGs) has lately begun receiving attention. As a successful means for developing new products, the quality function deployment (QFD) has been widely used in devising virtual items. In traditional QFD, information about the customers' needs and their priorities can be gained through some marketing methods. However, these approaches heavily rely on the subjective results and cannot identify the demands of each customer because of bewildering amount of information. Thus, we adopt the genetic chaotic neural network (GCNN) technique to identify each customer's needs and their priorities and propose the enhanced qualify function deployment (EQFD). However, in most of the existing literature, the equations to describe chaos dynamics are fixed and rigid corresponding to different nonlinear dynamic systems. In fact, for many chaotic systems in applications, it is often difficult to obtain accurate and faithful mathematical models, regarding their physically complex structures and hidden parameters. Therefore, GCNN is proposed in this paper, where GA is embedded into the chaotic neural network to generate and refine the equations of chaotic systems. By experimenting our methods with several benchmark methods, the proposed GCNN is found to demonstrate a clear advantage over other identifying methods, and EQFD is proven to be a feasible technique for developing the virtual items in MMORPGs.