The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In the distillation process, many important process variables are often difficult to be measured online. For example, the aviation kerosene is an important index of operation quality, but current methods cannot obtain the real-time value of the aviation kerosene efficiently. To solve this problem, a method of selecting the input variable based on partial least squares regression (PLS) is proposed...
In order to develop a fault diagnosis strategy in tramway environment, multiclass relevance vector machine (mRVM) based fault diagnosis strategy for proton exchange membrane fuel cell (PEMFC) of hybrid tramway is proposed. The method can quickly identify three kinds of fault states, such as the low hydrogen pressure, the low pressure of deionized water humidification pump and the bus communication...
A convenient way for controlling household appliances using a remote controller is not suitable for movement-disabled patients. To provide an alternative for such people, some applications on controlling household devices have been developed recently. However, there are some shortcomings in those control systems. Because the brain activities are reserved in movement-disabled patients, we proposed...
P300-speller which relies on P300-event related potential (ERP) is an important application of the BCI system. However, the accuracy and information transmission rate were relatively low for practical use. To solve the problem, researchers focused on two aspects of paradigms and classifiers. P300-speller with familiar face paradigm achieved a better performance. In addition, Bayesian linear discriminate...
In terms of divers equipped with open-circuit respirator, this paper studies the radiated mechanism of the divers' breathing signals. A SVM(Support Vector Machine) based approach to identify their radiated signal is proposed. In this method, the received signal is firstly processed using STFT(short-time Fourier transform). Then, the energy characteristics for sub-bands associated with the remarkable...
P300-speller is a communication system based on brain-computer interface (BCI) which allows users to input characters by focused attention. Support vector machine (SVM) ensemble has been successfully applied to classify in the P300-speller. However, large scale of training data was needed for the sub-classifiers to ensure the performance of classification. Subjects gradually got fatigue during the...
Least squares support vector machine (LS-SVM) has been successfully applied in many classification and regression tasks. The main drawback of the LS-SVM algorithm is the lack of sparseness. Combing the primal least squares twin support vector machine (LS-TSVM) and the sparse LS-SVM with L0-norm minimization, a new sparse least squares support vector regression algorithm with L0-norm in primal space(L...
P300-speller is a communication style based on Brain-computer interface (BCI) which allows users to input characters by electroencephalography (EEG) signals. In the past few years, there are various studies on P300-speller paradigm and classification algorithm. However, the accuracy and bit rates are not yet satisfied for our daily life. In order to improve the performance of the P300-speller, we...
In recent years, the support vector regression model (SVR) has been widely used to solve nonlinear regression and time series problems. The paper proposes short-term traffic forecasting model based on support vector regression, the traffic volumes at preceding periods of time and upstream and downstream are considered as input, traffic volumes at current period of time are considered as output. The...
This paper introduces Sphere Support Vector Machines (SVMs) as the new fast classification algorithm based on combining a minimal enclosing ball approach, state of the art nearest point problem solvers and probabilistic techniques. The blending of the three significantly speeds up the training phase of SVMs and also attains practically the same accuracy as the other classification models over several...
Discriminative Training (DT) methods for acoustic modeling, such as MMI, MCE, and SVM, have been proved effective in speaker recognition. In this paper we propose a DT method for GMM using soft frame margin estimation. Unlike other DT methods such as MMI or MCE, the soft frame margin estimation attempts to enhance the generalization capability of GMM to unseen data in case the mismatch exists between...
Support Vector Machine (SVM) is one of the most popular tools for solving general classification and regression problems because of its high predicting accuracy. However, the training phase of nonlinear kernel based SVM algorithm is a computationally expensive task, especially for large datasets. In this paper, we propose an intelligent system to solve large classification problems based on parallel...
Dry point of aviation kerosene in the atmospheric distillation column is a very important process value for quality controlling. But unfortunately few on-line hardware sensors are available to this value or such sensors are difficult to maintain. This paper adopts a novel method based on least squares support vector machine (LS-SVM) regression to implement on-line estimation of aviation kerosene dry...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.