Speed up grid-search for kernels selection of support vector regression

The aerobic granular sludge (AGS) is a one of the promising technologies for wastewater treatment. In this paper, several modelling strategies are developed to predict the behaviour of AGS. The modelling approaches are cautiously chosen to address the complex dynamic of AGS due internal interactions...

Full description

Saved in:

Bibliographic Details
Main Authors:	Ahmad Yasmin, Nur Sakinah, Abdul Wahab, Norhaliza, Danapalasingam, Kumerasan A.
Format:	Conference or Workshop Item
Published:	2022
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/98598/ http://dx.doi.org/10.1007/978-981-19-3923-5_46
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Speed up grid-search for Kernels selection of support vector regression
by: Ahmad Yasmin, Nur Sakinah, et al.
Published: (2022)

A hybrid technique for selecting support vector regression parameters based on a practical selection method and grid search procedure
by: Rana, Sohel, et al.
Published: (2016)

Improved support vector machine using optimization techniques for an aerobic granular sludge
by: Yasmin, Nur Sakinah Ahmad, et al.
Published: (2020)

Finding kernel function for stock market prediction with support vector regression
by: Chai, Chon Lung
Published: (2006)

Support vector regression modelling of an aerobic granular sludge in sequential batch reactor
by: Yasmin, N. S. A., et al.
Published: (2021)

Smooth support vector regression (SSVR) modelling of self-compacting concrete properties
by: Hadiwidodo, Yoyok Setyo
Published: (2013)

Prediction of Soil Pore Water Pressure Using Polynomial Kernel Support Vector Machine
by: Muhd Hasbi, Muhamad Alif
Published: (2017)

Prediction of Soil Pore Water Pressure Using Polynomial Kernel Support Vector Machine
by: Muhd Hasbi, Muhamad Alif
Published: (2017)

Flood forecasting of Malaysia Kelantan river using support vector regression technique
by: Faruq, Amrul, et al.
Published: (2021)

Support vector regression based friction modeling and compensation in motion control system
by: Tijani, Ismaila, et al.
Published: (2012)

Hourly photovoltaics power output prediction for Malaysia using support vector regression
by: Baharin, Kyairul Azmi, et al.
Published: (2015)

Fault location in an unbalanced distribution system using support vector classification and regression analysis
by: Gururajapathy, Sophi Shilpa, et al.
Published: (2017)

Development Of Construction Noise Prediction Method Using Linear Support Vector Regression Model
by: Gam, Li Juen
Published: (2021)

Prediction Of PM10 Concentration Using Multiple Linear Regression And Support Vector Machine
by: Zailan, Masezatti
Published: (2018)

An intelligent based-model role to simulate the factor of safe slope by support vector regression
by: Sari, Puteri Azura, et al.
Published: (2019)

Prediction of pm10 concentration using multiple linear regression and support vector machine
by: Zailan, Masezatti
Published: (2018)

Support vector regression and neural networks analytical models for gas sensor based on molybdenum disulfide
by: Alizadeh, Azar, et al.
Published: (2019)

Kernel methods and support vector machines for handwriting recognition
by: Ahmad A.R., et al.
Published: (2023)

Assimilation of principal component analysis and wavelet with kernel support vector regression for medium-term financial time series forecasting
by: Alhassan, Baba Gimba, et al.
Published: (2020)

Fiber fault monitoring for passive optical network using a kernel-based support vector machine
by: Usman, Auwalu, et al.
Published: (2021)

Improving grasshopper optimization algorithm for hyperparameters estimation and feature selection in support vector regression
by: Algamal, Zakariya Yahya, et al.
Published: (2021)

Fixed parameters Support Vector Regression for outlier detection
by: Rana, Sohel, et al.
Published: (2018)

Classification and regression analysis using support vector machine for classifying and locating faults in a distribution system
by: Gururajapathy, Sophi Shilpa, et al.
Published: (2018)

Prediction of meteorological drought by using hybrid support vector regression optimized with hho versus pso algorithms
by: Malik, Anurag, et al.
Published: (2021)

Comparative Study of Hybrid Support Vector Regression Drought Forecasting Models for Langat River Basin
by: Fung, Kit Fai
Published: (2018)

Weighted kernel regression in solving small sample problems for regression framework and its variants
by: Shapiai @ Abd. Razak, Mohd. Ibrahim
Published: (2014)

Prediction of cantilever retaining wall stability using optimal kernel function of support vector machine
by: Rohaya Alias, et al.
Published: (2021)

Time series support vector regression models with missing data treatments for water lavel prediction
by: Ibrahim, Noraini
Published: (2014)

Composite kernels for support vector classification of hyper-spectral data
by: Kohram, Mojtaba, et al.
Published: (2008)

VAR and GSTAR-BASED feature selection in support vector regression for multivariate spatio-temporal forecasting
by: Prastyo, D. D., et al.
Published: (2019)

Experimental and modelling of alkali-activated mortar compressive strength using hybrid support vector regression and genetic algorithm
by: Al-Sodani, Khaled A. Alawi, et al.
Published: (2021)

Experimenting the aplicability of support vector machine regression in rainfall prediction
by: Sulaiman, Junaida
Published: (2005)

Elastic net for single index support vector regression model
by: Dhhan, Waleed, et al.
Published: (2017)

Recipe generation from small samples by weighted kernel regression
by: Shapiai, Mohd. Ibrahim, et al.
Published: (2011)

Performance evaluation of vector evaluated gravitational search algorithm
by: Muhammad, B., et al.
Published: (2015)

Prediction of soluble solid content of starfruit using spectral imaging combined with partial least squares and support vector regression
by: Candra, F., et al.
Published: (2016)

Support vector regression-based model for prediction of behavior stone column parameters in soft clay under highway embankment
by: Aljanabi, Qasim A., et al.
Published: (2018)

The effect of kernel functions on cryptocurrency prediction using support vector machines
by: Hitam, Nor Azizah, et al.
Published: (2021)

The effect of Kernel functions on cryptocurrency prediction using support vector machines
by: Hitam, Nor Azizah, et al.
Published: (2022)

The effect of kernel functions on cryptocurrency prediction using support vector machines
by: Hitam, Nor Azizah, et al.
Published: (2022)