Samanta C.K.,Electrical Engineering |
Hota M.K.,Mathematics |
Hota M.K.,KIIT University |
Nayak S.R.,Economics |
And 2 more authors.
International Journal of Sustainable Engineering | Year: 2014
This paper deals with energy management in hybrid electric vehicles. Use of radial basis function neural network (RBFNN) for the problem of energy management gains importance in the present decade. Use of genetic algorithm (GA) and particle swarm optimization (PSO) as optimization algorithms for parameter estimation is also well known. However, none of the researchers in the area tried to use GA and PSO as training algorithms for the problem. Hence in this paper, we propose two novel methods, based on RBFNN. The difference between RBFNN-based approaches in the literature and those used in this paper is the use of GA and PSO (i.e. optimising algorithms) as training algorithm to train RBFNNs. Interestingly, it is seen that the proposed approaches of this paper outperform RBFNN-based approaches in the literature with traditional training. © 2014, © 2014 Taylor & Francis.
SIAM Journal on Optimization | Year: 2011
We give two self-dual regularizations of maximal monotone operators on Hilbert spaces. These regularizations and their set-valued inverses are strongly monotone, single-valued, and Lipschitz with full domain. Moreover, these regularizations graphically converge to the original monotone operator. If a maximal monotone operator has nonempty zeros, these self-dual regularizations can be used to find its least norm solution. When the maximal monotone operator is the subdifferential of a proper lower semicontinuous convex function with nonempty minimizers, this translates to finding the least norm minimizer. © 2011 Society for Industrial and Applied Mathematics.
AI and Society | Year: 2013
Following up on Thomas Nagel's paper "What is it like to be a bat?" and Alan Turing's essay "Computing machinery and intelligence," it shall be claimed that a successful interaction of human beings and autonomous artificial agents depends more on which characteristics human beings ascribe to the agent than on whether the agent really has those characteristics. It will be argued that Masahiro Mori's concept of the "uncanny valley" as well as evidence from several empirical studies supports that assertion. Finally, some tentative conclusions concerning moral implications of the arguments presented here shall be drawn. © 2013 Springer-Verlag London.
Ngabonziza Y.,Mathematics |
Li J.,City College of New York
ASME 2011 International Mechanical Engineering Congress and Exposition, IMECE 2011 | Year: 2011
In the past years, carbon nanotubes and their composites have been intensively studied due to their extremely high strength and high electrical and thermal conductivities. However, to be able to use CNT-reinforced composites as structural materials in real applications, more cost-efficient processing methods should be adopted and the properties of such nanocomposites need to be further analyzed. Here we investigate the electrical and elastic properties of multi-walled carbon nanotubes (MWCNT) reinforced polycarbonate (PC) nanocomposites produced by injection molding which has been widely used in industrial plastic production. Nanocomposite samples with MWCNT ranging from 0 to 7wt% were tested for both electrical conductivity using a 2-probe measurement and mechanical properties under tensile loading. It has been found that the electrical conductivity depends on both injection velocity and the CNT content while the elastic properties of the nanocomposites only depend on the CNT content. Besides the experimental testing, a percolation theory and micromechanics models have been applied to determine the electrical conductivity percolation threshold and the effective elastic modulus of the nanocomposites in terms of CNT contents. The results are compared with our experimental data. It shows that a percolation threshold is around 1.8wt % of MWCNT. The evaluation of elastic properties using micromechanics models not only indicates the influence of MWCNT on elastic properties but also the presence of an interphase between the CNT and PC matrix. Copyright © 2011 by ASME.
Saussie D.,Ecole Polytechnique de Montreal |
Barbes Q.,Mathematics |
Proceedings of the American Control Conference | Year: 2013
This paper presents a new application of structured H∞ synthesis to tune self-scheduled controllers. Newly available MATLAB-based tools allow to tune fixed-structure linear controllers while satisfying H ∞ constraints. Moreover multi-model synthesis capabilities can extend their application to self-scheduled controllers. This technique is successfully applied to the attitude control of a launch vehicle in atmospheric ascent phase. © 2013 AACC American Automatic Control Council.