Large Population Size IGAs with Individuals' Fitness Not Assigned by User
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
User-centric image segmentation using an interactive parameter adaptation tool
Pattern Recognition
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Interactive genetic algorithms with variational population size
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Interactive modelling for natural resource management
Environmental Modelling & Software
ConBreO: a music performance rendering system using hybrid approach of IEC and automated evolution
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Large population size IGA with individuals' fitness not assigned by user
Applied Soft Computing
Interactive genetic algorithms with individual's fuzzy fitness
Computers in Human Behavior
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Interactive genetic algorithms with large population and semi-supervised learning
Applied Soft Computing
Interactive evolutionary computation for analyzing human awareness mechanisms
Applied Computational Intelligence and Soft Computing - Special issue on Awareness Science and Engineering
Triple and quadruple comparison-based interactive differential evolution and differential evolution
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII
Learning aesthetic judgements in evolutionary art systems
Genetic Programming and Evolvable Machines
An IGA-based design support system for realistic and practical fashion designs
Computer-Aided Design
Crossover method for interactive genetic algorithms to estimate multimodal preferences
Applied Computational Intelligence and Soft Computing
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An interactive evolutionary computation (EC) fitting method is proposed that applies interactive EC to hearing aid fitting and the method is evaluated using a hearing aid simulator with human subjects. The advantages of the method are that it can optimize a hearing aid based on how a user hears and that it realizes whatever+whenever+wherever (W3) fitting. Conventional fitting methods are based on the user's partially measured auditory characteristics, the fitting engineer's experience, and the user's linguistic explanation of his or her hearing. These conventional methods, therefore, suffer from the fundamental problem that no one can experience another person's hearing. However, as interactive EC fitting uses EC to optimize a hearing aid based on the user's evaluation of his or her hearing, this problem is addressed. Moreover, whereas conventional fitting methods must use pure tones and bandpass noise for measuring hearing characteristics, our proposed method has no such restrictions. Evaluating the proposed method using speech sources, we demonstrate that it shows significantly better results than either the conventional method or the unprocessed case in terms of both speech intelligibility and speech quality. We also evaluate our method using musical sources, unusable for evaluation by conventional methods, and demonstrate that its sound quality is preferable to the unprocessed case