We introduce and formalize the multilevel classification problem, in which each category can be subdivided into different levels. We analyze the framework in a Bayesian setting using Normal class conditional densities. Within this framework, a natural monotonicity hint converts the problem into a nonlinear programming task, with non-linear constraints. We present Monte Carlo and gradient based ...

This paper presents an extension of Bayesian networks (BN) applied to reliability analysis of an open gas generator cycle Liquid propellant engine (OGLE) of launch vehicles. There are several methods for system reliability analysis such as RBD, FTA, FMEA, Markov Chains, and etc. But for complex systems such as LV, they are not all efficiently applicable due to failure dependencies between compo...

Multilevel inverters with space vector pulse width modulation strategy are gained importance in high power high performance industrial drive applications.This paper presents a simplified space vector PWM method for a two-level and three level inverter The threelevel inverter has a large number of switching states as compared to two level inverter. In the proposed scheme, three-level space vecto...

The Multilevel Inverter topology is advantageous in high-power and power-quality demanding application without use of transformer with reduced harmonic distortion. This paper explain the basic type of Multilevel Inverter such as diode clamped multilevel inverter (neutral point clamped), flywheel capacitor multilevel inverter (capacitor clamped), cascade multilevel inverter also the modulation a...

We propose and compare two approaches for regression analysis of multilevel binary data when clusters are not necessarily nested: a GEE method that relies on a working independence assumption coupled with a three-step method for obtaining empirical standard errors, and a likelihood-based method implemented using Bayesian computational techniques. Implications of time-varying endogenous covariat...

In this paper, a multilevel correction scheme is proposed to solve the Steklov eigenvalue problem by nonconforming finite element methods. With this new scheme, the accuracy of eigenpair approximations can be improved after each correction step which only needs to solve a source problem on finer finite element space and an Steklov eigenvalue problem on the coarsest finite element space. This co...

The purpose of this work is to identify a linear time-invariant dynamic model of wastewater treatment plants with multilevel pseudo random signals as an excitation input. The plants naturally aim to remove suspended substances, organic material and phosphate. An activated sludge process becomes the best technology available to control the discharge of pollutants. For this purpose, state-space m...

We present a model hierarchy multilevel optimisation approach to solve an optimal boundary control problem in glass manufacturing. The process is modelled by radiative heat transfer and formulated as an optimal control problem restricted by partial differential algebraic equations (PDAE) and additional control constraints. We consider a sequence of model approximations given by spacetime depend...

We consider the multilevel paradigm and its potential to aid the solution of combinatorial optimisation problems. The multilevel paradigm is a simple one, which involves recursive coarsening to create a hierarchy of approximations to the original problem. An initial solution is found and then iteratively refined at each level, coarsest to finest. Although the multilevel paradigm has been in use...

This study presents space vector-based quasi-two-level operation of a diode-clamped multilevel inverter which improves dc link utilisation and output voltage quality, and avoids the dc link capacitor voltage balancing problem experienced with standard multilevel operation. Beside a review of quasi-two-level operation and the capacitor voltage balancing method, the study presents a detailed disc...