Prediksi harga material konstruksi menjadi salah satu metode untuk membantu perkembangan dunia di Indonesia. Sebanyak 85% dari total biaya merupakan material, sedangkan sisanya alat dan tenaga kerja. Material sering kali berkaitan dengan makroekonomi maupun komoditas baik secara nasional internasional. dilakukan menggunakan Least Squares Support Vector Machine (LS-SVM) variabel input berupa dat...

This paper presents a new approach called clustering technique-based least square support vector machine (CT-LS-SVM) for the classification of EEG signals. Decision making is performed in two stages. In the first stage, clustering technique (CT) has been used to extract representative features of EEG data. In the second stage, least square support vector machine (LS-SVM) is applied to the extra...

Least squares support vector machines (LS-SVM) is an SVM version which involves equality instead of inequality constraints and works with a least squares cost function. In this way, the solution follows from a linear Karush–Kuhn–Tucker system instead of a quadratic programming problem. However, sparseness is lost in the LS-SVM case and the estimation of the support values is only optimal in the...

BACKGROUND In this work, near infrared spectroscopy (NIR) and an acoustic measure (AWETA) (two non-destructive methods) were applied in Prunus persica fruit 'Calrico' (n = 260) to predict Magness-Taylor (MT) firmness. METHODS Separate and combined use of these measures was evaluated and compared using partial least squares (PLS) and least squares support vector machine (LS-SVM) regression met...

This study investigated the feasibility of using hyperspectral imaging technique for nondestructive measurement of color components (ΔL*, Δa* and Δb*) and classify tea leaves during different drying periods. Hyperspectral images of tea leaves at five drying periods were acquired in the spectral region of 380-1030 nm. The three color features were measured by the colorimeter. Different preproces...

In this paper, an Optimally Pruned Extreme Learning Machine (OP-ELM) is applied to the problem of long-term time series prediction. Three known strategies for the long-term time series prediction i.e. Recursive, Direct and DirRec are considered in combination with OP-ELM and compared with a baseline linear least squares model and Least-Squares Support Vector Machines (LS-SVM). Among these three...

In this paper, two classifiers are proposed to distinguish between bulking and nonbulking situations in an activated sludge wastewater treatment plant, based on available image analysis information. The first classifier consists of a simple linear classification function, while the second classifier uses a highly nonlinear least squares support vector machine (LS-SVM) to distinguish between bot...

Because of the limited number of monitoring points on the ground, the accuracy of traditional monitoring methods using remote sensing was lower. This paper proposed to use the Least Squares Support Vector Machine (LS-SVM) theory to improve the accuracy of water quality retrieval, which is suitable for the small-sample fitting. The Radial Basic Function (RBF) was chosen as the kernel function of...

In this article we introduce a software framework for embedded online data fusion on different levels of data abstraction. We present our data oriented fusion model and introduce the main functional units. The paper is focused to the decision modeling process. In our approach we use Support Vector Machines (SVM) as well as Least Squares SVM (LS-SVM) for decision modeling. Due to the computation...

One of the main problems facing accurate location in wireless communication systems is non-line-ofsight (NLOS) propagation. Though learning location methods perform well in NLOS environments, learning location methods may be improved further since these methods do not consider outliers in the training data set. In this paper, we extend weighted least squares support vector machine (WLS-SVM) alg...