An intelligent swarm based-wavelet neural network for affective mobile phone design
Access Status
Authors
Date
2014Type
Metadata
Show full item recordCitation
Source Title
ISSN
School
Remarks
NOTICE: this is the author’s version of a work that was accepted for publication in Neurocomputing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Neurocomputing, Vol. 142 (2014). DOI: 10.1016/j.neucom.2014.01.054
Collection
Abstract
In this paper, an intelligent swarm based-wavelet neural network for affective mobile designed is presented. The contribution on this paper is to develop a new intelligent particle swarm optimization (iPSO), where a fuzzy logic system developed based on human knowledge is proposed to determine the inertia weight for the swarm movement of the PSO and the control parameter of a newly introduced cross-mutated operation. The proposed iPSO is used to optimize the parameters of wavelet neural network. An affective design of mobile phones is used to evaluate the effectiveness of the proposed iPSO. It has been found that significantly better results in a statistical sense can be obtained by the iPSO comparing with the existing hybrid PSO methods.
Related items
Showing items related by title, author, creator and subject.
-
Mostafa, Fahed. (2011)Market risk refers to the potential loss that can be incurred as a result of movements inmarket factors. Capturing and measuring these factors are crucial in understanding andevaluating the risk exposure associated with ...
-
Badrzadeh, Honey; Sarukkalige, Priyantha; Jayawardena, A. (2012)Achieving accurate intermittent river flow forecasting, plays a key role in water resources and environmental management. Water demands are increasing while surface water availability is likely to decrease in Western ...
-
Chan, Kit Yan; Khadem, Saghar; Dillon, Tharam (2012)Neural networks have been applied for short-term traffic flow forecasting with reasonable accuracy. Past traffic flow data, which has been captured by on-road sensors, is used as the inputs of neural networks. The size ...