The impact of reliable estimation of stream flows at highly urbanized areas and the associated receiving waters is very important for water resources analysis and design. We used the least squares support vector machine (LS-SVM) based algorithm to forecast the future streamflow discharge. A Gaussian Radial Basis Function (RBF) kernel framework was built on the data set to optimize the tuning pa...

Recently, a new type of neural networks called Least Squares Support Vector Machines (LS-SVMs) has been receiving increasing attention in nonlinear system identification and control due to its generalization performance. This paper develops a stable adaptive control scheme using the LS-SVM network. The developed control scheme includes two parts: the identification part that uses a modified str...

The contents of hemicellulose, cellulose and lignin are important for moso bamboo processing in biomass energy industry. The feasibility of using near infrared (NIR) spectroscopy for rapid determination of hemicellulose, cellulose and lignin was investigated in this study. Initially, the linear relationship between bamboo components and their NIR spectroscopy was established. Subsequently, succ...

As a latest multiresolution analysis method, curvelet transform has improved directional elements with anisotropy and better ability to represent sparsely edges and other singularities along curves. To reduce the dimensionality of facial image and improve the recognition rate, a face recognition system based on curvelet transform and Least Square Support Vector Machine (LS-SVM) has been develop...

Spirometry test is an inevitable, essential screening test in the case of respiratory and lung related diseases. This work focuses on predicting FEV1, which is the most significant and one of the deciding value in making the conclusion on respiratory related disorders by Least Squares Support Vector Machine (LS SVM) regression. This prediction of FEV1 values will enhance the spirometric method,...

Résumé. Les algorithmes de boosting de Newton Support Vector Machine (NSVM), Proximal Support Vector Machine (PSVM) et Least-Squares Support Vector Machine (LS-SVM) que nous présentons visent à la classification de très grands ensembles de données sur des machines standard. Nous présentons une extension des algorithmes de NSVM, PSVM et LS-SVM, pour construire des algorithmes de boosting. A cett...

In order to maintain a relatively high accuracy of navigation performance during global positioning system (GPS) outages, a novel robust least squares support vector machine (LS-SVM)-aided fusion methodology is explored to provide the pseudo-GPS position information for the inertial navigation system (INS). The relationship between the yaw, specific force, velocity, and the position increment i...

High blood pressure (BP) is associated with an increased risk of cardiovascular diseases. Therefore, optimal precision in measurement of BP is appropriate in clinical and research studies. In this work, anthropometric characteristics including age, height, weight, body mass index (BMI), and arm circumference (AC) were used as independent predictor variables for the prediction of BP reactivity t...

In this Paper, five recent natural inspired algorithms are proposed to optimize and train Least SquareSupport Vector Machine (LS-SVM). These algorithms are namely, Flower Pollination Algorithm (FPA), Bat algorithm (BA), Modified Cuckoo Search (MCS), Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO). These algorithms are proposed to automatically select best free parameters comb...

Three chemometric methods; partial least squares regression (PLS), principal component regression (PCR) and least-squares support vector machines (LS-SVM) were applied for simultaneous determination of carbidopa and levodopa in synthetic mixtures and real samples. The simultaneous determination of these drugs is a difficult problem due to spectral interferences. The proposed methods were used f...