A Comparison of BA, GA, PSO, BP and LM for Training Feed forward Neural Networks in e-Learning Context
Koffka Khan,Ashok Sahai +1 more
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This work intends to show the superiority (time performance and quality of solution) of the new metaheuristic bat algorithm (BA) over other more ―standard‖ algorithms in neural network training.Abstract:
Training neural networks is a complex task of great importance in the supervised learning field of research. We intend to show the superiority (time performance and quality of solution) of the new metaheuristic bat algorithm (BA) over other more ―standard‖ algorithms in neural network training. In this work we tackle this problem with five algorithms, and try to over a set of results that could hopefully foster future comparisons by using a standard dataset (Proben1: selected benchmark composed of problems arising in the field of Medicine) and presentation of the results. We have selected two gradient descent algorithms: Back propagation and Levenberg- Marquardt, and three population based heuristic: Bat Algorithm, Genetic Algorithm, and Particle Swarm Optimization. Our conclusions clearly establish the advantages of the new metaheuristic bat algorithm over the other algorithms in the context of eLearning.read more
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Nature-Inspired Optimization Algorithms
TL;DR: This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences, and researchers and engineers as well as experienced experts will also find it a handy reference.
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Bat algorithm: literature review and applications
Xin-She Yang,Xingshi He +1 more
TL;DR: A timely review of the bat algorithm and its new variants and a wide range of diverse applications and case studies are reviewed and summarised briefly here.
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A survey on new generation metaheuristic algorithms
TL;DR: In this survey, fourteen new and outstanding metaheuristics that have been introduced for the last twenty years other than the classical ones such as genetic, particle swarm, and tabu search are distinguished.
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Metaheuristic design of feedforward neural networks
TL;DR: A broad spectrum of FNN optimization methodologies including conventional and metaheuristic approaches are summarized, which provides interesting research challenges for future research to cope-up with the present information processing era.
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Bat Algorithm: Literature Review and Applications
TL;DR: A review of the bat algorithm and its variants can be found in this article, where a wide range of diverse applications and case studies are also reviewed and summarized briefly in the article.
References
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Book
A technique for the measurement of attitudes
TL;DR: The instrument to be described here is not, however, indirect in the usual sense of the word; it does not seek responses to items apparently unrelated to the attitudes investigated, and seeks to measure prejudice in a manner less direct than is true of the usual prejudice scale.
Posted Content
A New Metaheuristic Bat-Inspired Algorithm
TL;DR: The Bat Algorithm as mentioned in this paper is based on the echolocation behavior of bats and combines the advantages of existing algorithms into the new bat algorithm to solve many tough optimization problems.
Book ChapterDOI
A New Metaheuristic Bat-Inspired Algorithm
TL;DR: The Bat Algorithm as mentioned in this paper is based on the echolocation behavior of bats and combines the advantages of existing algorithms into the new bat algorithm to solve many tough optimization problems.
EVALUACION DE LA USABILIDAD EN SITIOS WEB, BASADA EN EL ESTANDAR ISO 9241-11 (International Standard (1998) Ergonomic requirements For office work with visual display terminals (VDTs)-Parts II: Guidance on usability
TL;DR: Galvis et al. as mentioned in this paper present una investigación en el campo de the Usabilidad in the Web, i.e., the problem of finding the productos mas eficientes, efectivos, and satisfactorios for usuarios.
Journal ArticleDOI
Usability, quality, value and e-learning continuance decisions
TL;DR: The proposed decomposed EDT model is proposed, which suggests that users' continuance intention is determined by satisfaction, which in turn is jointly determined by perceived usability, perceived quality, perceived value, and usability disconfirmation.