Medical & biological engineering & computing
Jul 8, 2017
Neurofeedback training teaches individuals to modulate brain activity by providing real-time feedback and can be used for brain-computer interface control. The present study aimed to optimize training by maximizing engagement through goal-oriented ta...
BACKGROUND: Intuitionistic fuzzy sets (IFS) represent a methodology for quantifying latent variables in questionnaire analysis through membership and non-membership functions, which are linked by an uncertainty function.
The robotic surgical platform is being utilized by a growing number of hospitals across the country, including academic medical centers. Training programs are tasked with teaching their residents how to utilize this technology. To this end, we have d...
Computational intelligence and neuroscience
Jan 31, 2016
Recently, teaching-learning-based optimization (TLBO), as one of the emerging nature-inspired heuristic algorithms, has attracted increasing attention. In order to enhance its convergence rate and prevent it from getting stuck in local optima, a nove...
This paper presents an empirical study of a formative neural network-based assessment approach by using mobile technology to provide pharmacy students with intelligent diagnostic feedback. An unsupervised learning algorithm was integrated with an aud...
Computational intelligence and neuroscience
Jan 14, 2016
An improved teaching-learning-based optimization with combining of the social character of PSO (TLBO-PSO), which is considering the teacher's behavior influence on the students and the mean grade of the class, is proposed in the paper to find the glo...
Computational intelligence and neuroscience
Sep 2, 2015
Teaching-learning-based optimization (TLBO) algorithm is proposed in recent years that simulates the teaching-learning phenomenon of a classroom to effectively solve global optimization of multidimensional, linear, and nonlinear problems over continu...
Computational intelligence and neuroscience
Aug 31, 2015
A comprehensive review on the problem of choosing a suitable activation function for the hidden layer of a feed forward neural network has been widely investigated. Since the nonlinear component of a neural network is the main contributor to the netw...
IEEE transactions on neural networks and learning systems
Oct 13, 2014
This paper presents the Chebyshev neural network (ChNN) as an improved artificial intelligence technique for power system protection studies and examines the performances of two ChNN learning algorithms for fault classification of series compensated ...
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