Reliable measurements of effluent quality are important for different operational tasks such as process monitoring, online simulation, and advanced control in the wastewater treatment process (WWTP). A kernel principal component analysis (KPCA) and extreme learning machine (ELM) based ensemble soft sensing model for effluent quality prediction was proposed. KPCA was used to extract nonlinear fe...

The most common optimization method for the of injection mold process parameters is range analysis, but there often a nonlinear coupling relationship between molding and quality indicators. Therefore, it difficult to find optimal combination in analysis. In this article, genetic algorithm optimized extreme learning machine network model (GA-ELM) combined with (GA) was proposed optimize mold. Ta...

We present a method for solving linear and nonlinear partial differential equations (PDE) based on the variable projection framework artificial neural networks. For PDEs, enforcing boundary/initial value problem collocation points gives rise to separable least squares about network coefficients. reformulate this by approach eliminate output-layer coefficients, leading reduced hidden-layer coeff...

Abstract Backbreak (BB) is one of the serious adverse blasting consequences in open-pit mines, because it frequently reduces economic benefits and seriously affects safety mines. Therefore, rapid accurate prediction BB great significance to mine design other production activities. For this purpose, six different swarm intelligence optimization (SIO) algorithms were proposed optimize extreme lea...

BACKGROUND The first aim of this study was to clarify the effective ratio of extractive from leaves of Morus Alba (ELM) to sucrose so as to apply this knowledge to the preparation of confections that could effectively suppress the elevation of postprandial blood glucose and insulin. The second aim was to identify the efficacy of confections prepared with the optimally effective ratio determined...

Extreme Learning Machine (ELM) algorithm not only has gained much attention of many scholars and researchers, but also has been widely applied in recent years especially when dealing with big data because of its better generalization performance and learning speed. The proposal of SS-ELM (semi-supervised Extreme Learning Machine) extends ELM algorithm to the area of semi-supervised learning whi...

Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto.fi Author Mark van Heeswijk Name of the doctoral dissertation Advances in Extreme Learning Machines Publisher School of Science Unit Department of Information and Computer Science Series Aalto University publication series DOCTORAL DISSERTATIONS 43/2015 Field of research Information and Computer Science Manuscript submitted 19 January 2...