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[PDF] Top 20 Modelling and control of PEMFC based on support vector machine

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Modelling and control of PEMFC based on support vector machine

Modelling and control of PEMFC based on support vector machine

... controller based on the support vector machine (SVM) model for the air flow control of the ...predictive control (MPC) strategy requires the system model to be as accurate as ... See full document

6

Support Vector Machine (SVM) aggregation modelling for spatio-temporal air pollution analysis

Support Vector Machine (SVM) aggregation modelling for spatio-temporal air pollution analysis

... and control air pollution analysis were too conventional and showed the indirect damage caused by it (Vlachokostas et ...is based on simple tests, and such tests are selected based on less or more ... See full document

186

Density-Based Multi Feature Background Subtraction with Support Vector Machine

Density-Based Multi Feature Background Subtraction with Support Vector Machine

... mathematician mixture model is that the Expectation Maximisation SVM algorithmic program. The SVM algorithmic program is Associate in Nursing unvaried technique that guarantees to converge to a local most in a very ... See full document

10

Support Vector Machine Based Tool for Plant Species Taxonomic Classification

Support Vector Machine Based Tool for Plant Species Taxonomic Classification

... taxonomy is taken into consideration for data modelling. The customized binary classifiers are trained with specific features at each node. Top to bottom approach is used for identifying taxonomic information like ... See full document

15

The Fracture Density and Fractal Dimension Prediction Based on Support Vector Machine

The Fracture Density and Fractal Dimension Prediction Based on Support Vector Machine

... and support vec- tor machine, and compute fracture density, fractal di- mension of wells that lack core and imaging logging ...under control of several ... See full document

8

Sliding Mode Control based Support Vector Machine RBF Kernel Parameter Optimization

Sliding Mode Control based Support Vector Machine RBF Kernel Parameter Optimization

... Mode Control (SMC) is a powerful technique for controlling a non-linear system, particularly when there is not a precise mathematical model for the system or the model does not represent all system’s parameters ... See full document

6

Classification of ripening stages of bananas based on support vector machine

Classification of ripening stages of bananas based on support vector machine

... Since RS is directly related to banana quality, to detect and control RS of banana is very important in fruit industry, and rapid detection of RS of banana is required in quality control [12] . Most of the ... See full document

6

Based on Support Vector Machine of Cold Rolling Force Prediction Research

Based on Support Vector Machine of Cold Rolling Force Prediction Research

... process control model, and its prediction accuracy directly affects the predicted values of other models such as rolling moment, so the study of the rolling force prediction model in the tandem cold rolling ... See full document

8

Support Vector Machine-Based Classification of AD on Bootstrap Method

Support Vector Machine-Based Classification of AD on Bootstrap Method

... Support Vector Machines (SVM) has recently been used to help distinguish AD subjects from elderly control subjects using anatomical MR imaging ...to control subjectsor to help differentiate AD ... See full document

6

Support vector machine and its difficulties from control field of view

Support vector machine and its difficulties from control field of view

... be chosen in a way to satisfy this condition. Consequently, Radial Basis Function (RBF) or polynomial kernels are used to determine learning gain for each input misclassified data, creating a linear weighting combination ... See full document

23

FPGA-Based Cascade Support Vector Machine with Integrated Training

FPGA-Based Cascade Support Vector Machine with Integrated Training

... Therefore to save as more time as possible, one way is to speedup the reading process from a CF card to BRAMs. A subset is read firstly and the computation process is started. The control system loads the data to ... See full document

81

Sliding Mode Control based Support Vector Machine

RBF Kernel Parameter Optimization

Sliding Mode Control based Support Vector Machine RBF Kernel Parameter Optimization

... where f(S) could be any non-decreasing odd function. This shows that the change in S and the 'distance' of the current state of the sliding surface, it is always opposite the sign of S. The control input should ... See full document

10

Quality control tracking of the graduate based on support vector machine theory

Quality control tracking of the graduate based on support vector machine theory

... quality control system was carried out, the third party evaluation to complete the teaching quality from the principal, process and result on careful analysis of data, and find the reasons to consider feedback, ... See full document

9

Congestion control in ATM-based Broadband ISDNs Using Support Vector Machine

Congestion control in ATM-based Broadband ISDNs Using Support Vector Machine

... congestion control for high speed communication networks can be ...This control law is transformed into discrete values and window form for ATM and ...are based on the output measurements of the ... See full document

8

From the Support Vector Machine to the Bounded Constraint Machine

From the Support Vector Machine to the Bounded Constraint Machine

... Our motivation for this paper is to modify the criterion of the SVM. Instead of the maximum separation criterion whose solution only depends on a subset of the training data, we propose to use an alternative criterion so ... See full document

14

Regression depth and support vector machine

Regression depth and support vector machine

... Binary regression and statistical machine learning play a key role in theoretical and applied statistics. In supervised learning we have a set of variables, say X (the predictors, the explanatory variables, or the ... See full document

16

Support vector machine and fraud detection

Support vector machine and fraud detection

... Nato smo nad podatki uporabili tudi metodo podpornih vektorjev enega razreda, pri kateri lahko s pomočjo parametra ν uravnavamo delež vseh podatkov, ki jih želimo dobiti kot osamelce.[r] ... See full document

79

Study on support vector machine as a classifier

Study on support vector machine as a classifier

... When the data becomes inseparable we use other kernel [9], [14], [15] functions instead of the linear kernel one for better classification. We are using Gaussian radial basis function [2] as a kernel for the non-linear ... See full document

39

Direct L2 Support Vector Machine

Direct L2 Support Vector Machine

... All the results presented in [12] and [22] serve as a starting point to a performance analysis shown here. Extensive investigations of SphereSVM and MN SVM imple- mented in open-source framework called GSVM - Command ... See full document

118

Distributed Support Vector Machine Learning

Distributed Support Vector Machine Learning

... The main problem with current day SVMs is that they cannot process large datasets in a timely manner. This problem is compounded further when multiple SVM training rounds are needed as with SVM clustering methods being ... See full document

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