Dynamic classifier selection: Recent advances and perspectives
Abstract Multiple Classifier Systems (MCS) have been widely studied as an alternative for
increasing accuracy in pattern recognition. One of the most promising MCS approaches is …
increasing accuracy in pattern recognition. One of the most promising MCS approaches is …
Gradient-based differential neural-solution to time-dependent nonlinear optimization
In this technical article, to seek the optimal solution to time-dependent nonlinear optimization
subject to linear inequality and equality constraints (TDNO-IEC), the gradient-based …
subject to linear inequality and equality constraints (TDNO-IEC), the gradient-based …
A new varying-parameter convergent-differential neural-network for solving time-varying convex QP problem constrained by linear-equality
To solve online continuous time-varying convex quadratic-programming problems
constrained by a time-varying linear-equality, a novel varying-parameter convergent …
constrained by a time-varying linear-equality, a novel varying-parameter convergent …
Reliable multiple combined fault diagnosis of bearings using heterogeneous feature models and multiclass support vector Machines
This paper proposes a reliable multiple combined fault diagnosis scheme for bearings using
heterogeneous feature models and an improved one-against-all multiclass support vector …
heterogeneous feature models and an improved one-against-all multiclass support vector …
Varying-parameter convergent-differential neural solution to time-varying overdetermined system of linear equations
Z Zhang, L Zheng, T Qiu, F Deng - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
To solve a time-varying overdetermined problem, a novel varying-parameter convergent-
differential neural network (VP-CDNN) is proposed, designed, and discussed. Specifically, a …
differential neural network (VP-CDNN) is proposed, designed, and discussed. Specifically, a …
Zhang neural network for online solution of time-varying convex quadratic program subject to time-varying linear-equality constraints
Y Zhang, Z Li - Physics Letters A, 2009 - Elsevier
In this Letter, by following Zhang et al.'s method, a recurrent neural network (termed as
Zhang neural network, ZNN) is developed and analyzed for solving online the time-varying …
Zhang neural network, ZNN) is developed and analyzed for solving online the time-varying …
DRCW-OVO: distance-based relative competence weighting combination for one-vs-one strategy in multi-class problems
One-vs-One strategy is a common and established technique in Machine Learning to deal
with multi-class classification problems. It consists of dividing the original multi-class …
with multi-class classification problems. It consists of dividing the original multi-class …
A survey of commonly used ensemble-based classification techniques
The combination of multiple classifiers, commonly referred to as a classifier ensemble, has
previously demonstrated the ability to improve classification accuracy in many application …
previously demonstrated the ability to improve classification accuracy in many application …
Combining multiple algorithms in classifier ensembles using generalized mixture functions
Classifier ensembles are pattern recognition structures composed of a set of classification
algorithms (members), organized in a parallel way, and a combination method with the aim …
algorithms (members), organized in a parallel way, and a combination method with the aim …
Novel layered clustering-based approach for generating ensemble of classifiers
This paper introduces a novel concept for creating an ensemble of classifiers. The concept is
based on generating an ensemble of classifiers through clustering of data at multiple layers …
based on generating an ensemble of classifiers through clustering of data at multiple layers …