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LEAST SQUARES SUPPORT VECTOR MACHINES PARAMETER OPTIMIZATION BASED ON IMPROVED ANT COLONY ALGORITHM FOR HEPATITIS DIAGNOSIS

Nursuci Putri Husain,Nursanti Novi Arisa,Putri Nur Rahayu,Agus Zainal Arifin,Darlis Herumurti

Many kinds of classification method are able to diagnose a patient who suffered Hepatitis disease. One of classification methods that can be used was Least Squares Support Vector Machines (LSSVM). There are two parameters that very influence to improve th... see more

Classification | Least Squares Support Vector Machines | Improved Ant Colony Algorithm | Local Fisher Discriminant Analysis | Hepatitis Disease

Jurnal Ilmu Komputer dan Informasi , 2017

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A Fuzzy Least Squares Support Tensor Machines in Machine Learning

Ruiting Zhang,Zhijian Zhou

In the machine learning field, high-dimensional data are often encountered in the real applications. Most of the traditional learning algorithms are based on the vector space model, such as SVM. Tensor representation is useful to the over fitting problem ... see more

Alternating projection | Least square support tensor machines | Support tensor machines | Tensor learning

International Journal of Emerging Technologies in Learning (iJET) , 2015

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Penerapan Least Squares Support Vector Machines (LSSVM) dalam Peramalan Indonesia Composite Index DOI: 10.32493/informatika.v6i1.10237

Andri Triyono,Rahmawan Bagus Trianto,Dhika Malita Puspita Arum

In the era of very rapidly advancing technology like today, both internet technology and computerization have made various corporate agencies or investors start thinking about the importance of the stock market in their capital division. Previously there ... see more

LSSVM | RBF Kernel | Stock Price | Prediction

Jurnal Informatika Universitas Pamulang , 2021

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Mean Shifts Diagnosis and Identification in Bivariate Process Using LS-SVM Based Pattern Recognition Model

zhiqiang cheng

This study develops a least squares support vector machines (LS-SVM) based model for bivariate process to diagnose abnormal patterns of process mean vector, and to help identify abnormal variable(s) when Shewhart-type multivariate control charts based on ... see more

multivariate statistical process control | least squares support vector machines | pattern recognition | quality diagnosis | bivariate process

International Journal of Industrial Engineering: Theory; Applications and Practice , 2013

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A New Two-Stage Approach to Short Term Electrical Load Forecasting

Miloš Božic, Miloš Stojanovic, Zoran Stajic and Dragan Tasic

In the deregulated energy market, the accuracy of load forecasting has a significant effect on the planning and operational decision making of utility companies. Electric load is a random non-stationary process influenced by a number of factors which make... see more

short-term load forecasting | least-squares support vector machines | average daily load | two-stage approach

Energies , 2013

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Using Principal Component Analysis and Least Squares Support Vector Machine to Predict the Silicon Content in Blast Furnace System

Shihua Luo,Tianxin Chen,Ling Jian

Blast furnace system is a typical example of complex industrial system. The silicon ([Si]) content in blast furnace system is an important index to reflect the temperature of furnace. Therefore, it is significant to carry out an accurate predictive contro... see more

blast furnace system | principal component analysis | least squares support vector machine | silicon content prediction

International Journal of Online Engineering (iJOE) , 2018

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USING A LEAST SQUARES SUPPORT VECTOR MACHINE TO ESTIMATE A LOCAL GEOMETRIC GEOID MODEL

SZU-PYNG KAO KAO,CHAO-NAN CHEN,HUI-CHI HUANG,YU-TING SHEN

In this study, test-region global positioning system (GPS) control points exhibitingknown first-order orthometric heights were employed to obtain the points of planecoordinates and ellipsoidal heights by using the real-time GPS kinematicmeasurement method... see more

Least Squares Support Vector Machine (LS-SVM) | Kernel Function | Local Geoid Model

Boletim de Ciências Geodésicas , 2014

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An EMD-Based Chaotic Least Squares Support Vector Machine Hybrid Model for Annual Runoff Forecasting

Xuehua Zhao, Xu Chen, Yongxin Xu, Dongjie Xi, Yongbo Zhang, Xiuqing Zheng

Accurate forecasting of annual runoff is necessary for water resources management. However, a runoff series consists of complex nonlinear and non-stationary characteristics, which makes forecasting difficult. To contribute towards improved prediction accu... see more

empirical mode decomposition | chaotic characteristics | phase space reconstruction | least squares support vector machine | runoff forecasting

Water , 2017

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Least Squares Support Vector Machine for Ranking Solutions of Multi-Objective Water Resources Allocation Optimization Models

Weilin Liu, Lina Liu, Fang Tong

There is an increasing trend in the use of multi-objective evolutionary algorithms (MOEAs) to solve multi-objective optimization problems of the allocation of water resources. However, typically the outcome is a set of Pareto optimal solutions which make ... see more

least squares support vector machine (LSSVM) | k-means clustering | artificial neural network (ANN) | water resources allocation

Water , 2017

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