Four rumen fistulated swamp buffaloes were randomly assigned according to a 4×4 Latin square design to investigate the effects of Eucalyptus (E. Camaldulensis) leaf meal (ELM) supplementation as a rumen enhancer on feed intake and rumen fermentation characteristics. The dietary treatments were as follows: T1 = 0 g ELM/hd/d; T2 = 40 g ELM/hd/d; T3 = 80 g ELM/hd/d; T4 = 120 g ELM/hd/d, respective...

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Extreme Learning Machine (ELM) as an emergent technology has shown its promising performance in many applications. This paper proposes a parallelized ELM ensemble based on the Min–Max Modular network (M-network) to meet the challenge of the so-called big data. The proposed M-ELM first decomposes classification problems into smaller subproblems, then trains an ELM for each subproblem, and in the...

Edge Localised Modes are characteristic of the high performance, H-mode plasmas that are required for the attainment of Q = 10/500MW fusion power in the first phase of ITER operation. The energy released by a type I ELM, in good confinement plasmas, is typically 510% of the plasma stored energy; with low collisionality plasmas at the upper end of the range. Dimensional analysis, experiment and ...

To address the imbalanced classification problem emerging in Bioinformatics, a boundary movement-based extreme learning machine (ELM) algorithm called BM-ELM was proposed. BM-ELM tries to firstly explore the prior information about data distribution by condensing all training instances into the one-dimensional feature space corresponding to the original output in ELM, and then on the transforme...

We propose and develop SG-ELM, a stable online learning algorithm based on stochastic gradients and Extreme Learning Machines (ELM). We propose SG-ELM particularly for systems that are required to be stable during learning; i.e., the estimated model parameters remain bounded during learning. We use a Lyapunov approach to prove both asymptotic stability of estimation error and boundedness in the...

The limiting velocity in open channels to prevent long-term sedimentation is predicted in this paper using a powerful soft computing technique known as Extreme Learning Machines (ELM). The ELM is a single Layer Feed-forward Neural Network (SLFNN) with a high level of training speed. The dimensionless parameter of limiting velocity which is known as the densimetric Froude number (Fr) is predicte...

A new image denoising algorithm is proposed. GA-ELM algorithm uses genetic algorithm (GA) to decide weights in the Extreme learning Machine algorithm. It has better global optimal characteristics than traditional optimal algorithm. In this paper, we used GA-ELM to do image denoising researching work. Firstly, this paper uses training samples to train GA-ELM as the noise detector. Then, we utili...

High-resolution quadrature reflectometer measurements of density fluctuation levels have been obtained on DIII-D for H-mode edge pedestal studies. Initial results are presented from the L–H transition to the first ELM for two cases: (i) a low pedestal beta discharge, in which density turbulence in the pedestal has little change during the ELM-free phase, and (ii) a high pedestal beta discharge ...