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In this paper we demonstrate an improvement in the transient tracking performance when a Support Vector Regression (SVR) is used to identify a nonlinear ARMA plant. We use an on-line version of SVR, and at each instant, the identified model is used to determine the appropriate control law. A further improvement in the transient performance is shown with the methodology of multiple models, switching,...
In this study, a hybrid model using multivariate adaptive regression splines (MARS) and SVR is proposed for sales forecasting of information technology (IT) products. Support vector regression (SVR) has become a promising alternative for forecasting due to its generalization capability in obtaining a unique solution. However, one of the key problems is that SVR can not identify which forecasting variables...
This paper presents experiments using several vector space models in Automated Essay Scoring (AES). Firstly, we compare four different Vector Space Models (VSM) which are the Word-based Vector Space Model (W-VSM), the Weight Adapted Word-based Vector Space Model (WAW-VSM), the Latent Semantic-based Vector Space Model (LS-VSM) and the Sequence Latent Semantic-based Vector Space Model (SLS-VSM). The...
The performance of a model, which is trained with offline data, is highly relied on the conditions in which the system is working. When the working conditions change, the prediction accuracy of the model will be reduced significantly. To solve this problem, we propose an adaptive SVR modeling method based on vector-field-smoothed (VFS) algorithm. This method can adapt the model quickly to new working...
The simultaneous identification of multiple nonlinear plants using support vector regressions, and the methodology of multiple models, switching, and tuning, is proposed in this paper. Models are randomly initialised and, at each instant, they are assigned to a specific nonlinear plant, and adapted toward it. Accordingly, the models self-organise themselves in a manner so that, at any given instant...
Yield is a very important criterion to measure the semiconductor wafer fabrication facilities (FABs) productivity. The finished products will be check by Wafer Acceptance Test (WAT) and Circuit Probe (CP) to classified into ferior goods or inferior goods. This research applied the data from WAT and CP for the selection of the most important measuring parameters to improve the yield. Three methods,...
This paper explores application of support vector regression to adaptive inverse control problems. Support vector regression (SVR) has been proven to generate global solutions contrary to neural networks, because SVR basically solves quadratic programming (QP) problems. With this advantage, a plant model is identified and its inverse model is learned. In addition, adaptive algorithms for compensating...
Modeling of rotary drying remains a challenging research topic due to the highly nonlinear and strongly interactive multivariable process. The first-principles model (white box) consisting of partial differential equations with several experimental parameters is very complex and the data-driven model (black box) is lack of transparency and the required depth and quality of industrial experimental...
Based on local audio feature and support vector regression (SVR), an adaptive blind audio watermarking algorithm in wavelet domain is proposed in this paper. The audio signal is partitioned into audio frames, and the watermark is embedded in wavelet domain. For each audio frame, the energy and the maximal peaks of its all sub-bands are extracted as the local features, and SVR is used to model the...
There is an increasing interest in more accurate prediction of software maintainability in order to better manage and control software maintenance. Recently, TreeNet has been proposed as a novel advance in data mining that extends and improves the CART (classification and regression trees) model using stochastic gradient boosting. This paper empirically investigates whether the TreeNet model yields...
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