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Intelligent non-linear modelling of an industrial winding process using recurrent local linear neuro-fuzzy networks

Journal of Zhejiang University-Science C(Computers and Electronics) 2012年第6期13卷 403-412页

作者： Hasan ABBASI NOZARI hamed dehghan banadaki Mohammad MOKHTARE Somayeh HEKMATI VAHED Department of Mechatronics Faculty of EngineeringIslamic Azad UniversityScience and Research BranchTehranIran

This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system. A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT), which is an incremental tree-based learning algorithm. The proposed NF models are compared with other known intelligent identifiers, namely multilayer perceptron (MLP) and radial basis function (RBF). Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system. Experimental results show the effectiveness of our proposed NF modelling approach.

关键词： Non-linear system identification Recurrent local linear neuro-fuzzy (RLLNF) network Local linear model tree(LOLIMOT) Neural network (NN) Industrial winding process

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Intelligent non-linear modelling of an industrial winding process using recurrent local linear neuro-fuzzy networks

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Frontiers of Information Technology & Electronic Engineering 2012年第9期 701-701页

作者： Hasan Abbasi Nozari hamed dehghan banadaki Mohammad Mokhtare Somayeh Hekmati Vahed

关键词： NF Intelligent non-linear modelling of an industrial winding process using recurrent local linear neuro-fuzzy networks

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A three-dimensional polyhedral unit model for grain boundary structure in fcc metals

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npj Computational Materials 2017年第1期3卷 361-373页

作者： Arash dehghan banadaki Srikanth Patala Department of Materials Science and Engineering North Carolina State UniversityRaleighNCUSA

One of the biggest challenges in developing truly bottom-up models for the performance of polycrystalline materials is the lack of robust quantitative structure-property relationships for *** a first step in analyzing such relationships,we present a polyhedral unit model to classify the geometrical nature of atomic packing along grain *** the atomic structure in disordered systems has been a topic of interest for many decades,geometrical analyses of grain boundaries has proven to be particularly challenging because of the wide range of structures that are possible depending on the underlying macroscopic crystallographic *** this article,we propose an algorithm that can partition the atomic structure into a connected array of three-dimensional polyhedra,and thus,present a three-dimensional polyhedral unit model for grain boundaries.A point-pattern matching algorithm is also provided for quantifying the distortions of the observed grain boundary polyhedral *** polyhedral unit model is robust enough to capture the structure of high-Σ,mixed character interfaces and,hence,provides a geometric tool for comparing grain boundary structures across the five-parameter crystallographic *** the obtained polyhedral units circumscribe the voids present in the structure,such a description provides valuable information concerning segregation sites within the grain *** anticipate that this technique will serve as a powerful tool in the analysis of grain boundary *** polyhedral unit model is also applicable to a wide array of material systems as the proposed algorithm is not limited by the underlying lattice structure.

关键词： enough boundary structure

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