vector machine

The results show that this method is feasible and the classification accuracy and speed is better than traditional support vector machine.

Pointed out that the concept of knowledge, general classification algorithms and support vector machine classifier.

However, as a newer theory of machine learning field, support Vector Machine is still being developed and constant improved.

The selection method of kernel in the information entropy support vector machine model is one of our in-depth researches.

Initial goal concept learned by standard support vector machine algorithm was updated by an updating model.

and a support vector machine regression (SVR) technique is introduced to establish the model of power equipment insulation status change.

Sub-clusters can predict by relevance vector machine, and increase arithmetic speed using a more effective kernel parameter choosing method.

Support Vector Machine is proven to be a novel approach to model the cutting depth of abrasive water jet.

With the combination with a Support Vector Machine, we design and implement the improved text classifier.

The last topic is about a trainable object detection system using at its core a Support Vector Machine classifier.

Information classification model established a face to face simple step-form of support vector machine web text classification.

Experimental result indicated that, support vector machine used in flight segment volume is effective.

The support vector machine(SVM)combined with the k-nearest neighbor(KNN)algorithm is applied to solar proton event prediction.

A sort of incremental learning algorithm for support vector machine based on clustering was proposed.

As the newest branch of statistic learning theory, support vector machine(SVM) have become increasingly popular tools.

This paper introduces the theory of support vector machine (SVM) arid applies it in image classification.

On this base, a novel segmentation algorithm using support vector machine is presented for segmentation.

Then, support vector machine is selected to classify aiming at clinical ECG data. Finally, classifications combination approach is analyzed.

The dissertation mainly aims at applying support vector machine (SVM) and kernel principal component analysis (KPCA) to intrusion detection.

Relevance Vector Machine (RVM) of the matlab source code, including the fast algorithm that contains the code instructions.

For improving the generalization performance of support vector machine(SVM) effectively, two ensemble algorithms are proposed to train SVM.

In this thesis, segmentation technique of support vector machine is analyzed and researched basic on partly main segmentation technique.

Support vector machine(SVM) is a study machine developing from statical learning theory, which has splendid regression feature.

The Support Vector Machine (SVM) method and its application to short-term load forecast are presented.

This paper majorly discussed the application of the support vector machine SVM in rice water requirement forecast.

Thus an approach that applied immune algorithm to optimize parameters of SVM (Support Vector Machine) and feature selection was proposed.

Support vector machine classification is realized by least square algorithm and numerical simulation is performed.

For this reason, several important properties of kernel function are discussed on the basis of support vector machine.

Experimental results show that support vector machine approach is a promising technique for image segmentation.

The combination of wavelet analysis and support vector machine is introduced to automatically diagnose power supply line fault.

The experiments show using fuzzy support vector machine significantly improves the overall recognition rate.

Min-Max Modular Support Vector Machine(M3-SVM) is an "divide and conquer" based algorithm which can effectively solve large-scale problems.

Artificial Neural Networks and Support Vector Machine were selected to test classification accuracy and the test results were analyzed.

Support vector machine, which has high precision of categorization and excellent generalization ability, is used to categorize text.

In response to above problems, this paper proposes a fracture-cave reservoir prediction method relying on support vector machine.

Then the characteristic was classified and predicted to generate semantic vector using support vector machine.

Finally, forecasting method based on support vector machine applies in the system of "Flight Optimization & Revenue Maximization" .

This paper introduces the machine learning procedure of training support vector machine by using linear particle swarm optimization.

Support Vector Machine(SVM) method is a surface fitting algorithm in a way.

After the feature vector is available, support vector machine(SVM) is used for classification.

The principle and algorithm of K- nearest neighbor, Naive Bayes, Support Vector Machine Nerve Network etc. are elaborated.

Support Vector Machine (SVM) is a new technique in data mining, but Support Vector Regression (SVR) is the applying of SM in regression.

In this study, Total-margin Adaptive Fuzzy Support Vector Machine (TAFSVM) of good quality was proposed.

Support Vector Machine is a new machine learning algorithm for classification and regression question.

The results shows that the Bayesian Belief Network has better performance than the Decision Tree and Support Vector Machine.

In this paper, the support vector machine method is used to forecast ice jam stage, and the results are accordant with the fact.

Support vector machine can reflect the complex mapping relation between input factors and the output results perfectly.

The model solved a convex quadratic programming similar to standard support vector machine algorithm.

To find out their relationship, this paper, support vector machine method, the data collected in different analysis of nuclear function.

Then, the parameters of reduced least squares vector machine are identified by kernel partial least squares.

The support vector machine based speaker verification models are trained on the enrolled speaker and the background model.

MissSVM package solution is to use multi-instance semi-supervised support vector machine learning problems.

And support vector machine model is used to estimate the unmeasured process parameters that are difficult to model with first principle.

Finally, support vector machine (SVM) was adopted for automatic determination for short-time sleep data.

A CEDT opportunities and support vector machine classification and face recognition.

It is studied the application of independent component analysis and support vector machine to fault diagnosis of induction motor.

At last, a personal preview of further tasks in the research realms of neural network and support vector machine is presented.

Support vector machine is a machine learning approach which has powerful ability to captive verge point.

A classification algorithm of non-linear support vector machine (SVM) decision tree is presented.

Support vector machine (SVM) and the neural network are both currently hot subject in the area of machine learning technology.

A novel method for fingerprint image segmentation using support vector machine was proposed.

The prediction results show that the prediction of traffic using the support vector machine (SVM) is feasible and effective.

The support vector machine (SVM) method is applied to forecast long-term run-off.

Aiming at the problem of classification of Time-Varying Signal patterns, this paper presents a Process Support Vector Machine (PSVM) model.

Presents support vector machine to solve the classification problem based on the fire video and suspected fire video.

It is confirmed that the support vector machine theory can predict the velocity of blasting vibration well.

A time series forecasting method based on dynamic weighted least squares support vector machine (LSSVM) is proposed.

In the pattern recognition strut vector machine , may use in the person face recognition training !

To solve the problem, an improved Local LSI (LLSI) method was proposed, using Support Vector Machine (SVM) to produce the local region.

Firstly, some critical issues about the nonlinear binary-class support vector machine (SVM) are studied.

Least square support vector machine (LS-SVM) is used to predict the trend of the aircraft flap system.

New sentences are then detected with Winnow andsupport vector machine classifiers, respectively.

and (3) acquiring results of hand motion classification and identification by adopting a method supporting a vector machine.

The uploaded Support Vector Machine (SVM) Classifier can classify text-type data well.

The paper mainly researches a traditional classifier: support vector machine (SVM) which is diffusely used in recent years.

Objective: This paper put forward for classifying cardiac arrhythmia signals based on ECG waveform features and support vector machine(SVM).

Support vector machine (SVM) is a novel pattern recognition technique.

Parameter selection of kernel function is an issue of nonlinear study based on Support Vector Machine (SVM).

Based on the theory of support vector machine (SVM), establishes a prediction model for building air conditioning load.

A method for selecting an optimal cost parameter C in support vector machine (SVM) is presented.

Furthermore, a hybrid system of Support Vector Machine (SVM) and Gaussian Mixed Model (GMM) is introduced.

However, the support vector machine, after all, a kind of new technology is not mature enough, there are many limitations.

This paper introduces a method to detect driver fatigue with support vector machine.

The experiment result proved that arithmetic of Support Vector Machine has the good effect in the text classification aspect.

Support vector machine (SVM) is a powerful machine learning technique based on statistical learning theory ( SLT ).

A support vector machine (SVM) model is used to correlate the false alarm of BIT to time stress information.

Absrtact: SVM (support vector machine) algorithm is the newest branch of statistic learning theory.

We emphases discussed the nearest neighbor classifier and support vector machine (SVM) based on the statistical study theory.

Another one is the intelligent forecasting model based on neural network, genetic algorithm, and support vector machine.

This paper presents an approach of rotor position estimation for switched reluctance motor based on support vector machine (SVM).

This paper proposes a detection method based on support vector machine based on analysis and comparison with several other methods.

A novel approach to fault diagnosis of rolling bearings based on Weibull distribution model and support vector machine is proposed.

Under the rationale of the time series forecast, the article produced a model that based on the time series support vector machine forecast.

A novel approach to micro-displacement detection of dams based on Support Vector Machine and coherence average denoising is pro posed.

In this paper a method based on support vector machine is presented, which can discover prediction knowledge from historical alarms.

More over, Support Vector Machine is also proposed for classification of small samples.

Focus on inferior product in plastic blister tablets'packing, an inspection method based on Support Vector Machine is proposed.

Based on the support vector machine method, a motion control algorithm for the spherical robot is introduced.

BVM(Ball Vector Machine)is a faster machine learning algorithm than SVM.

Finally, the paper gave the detailed design of support vector machine forecasting method based on support vector machine.

This thesis analyzes forecasting methods and makes research of flight segment volume based on support vector machine.

It is difficult to apply the standard quadratic model optimization in the realization of support vector machine.

To deal with customer churn problem in textile industry, this paper set up prediction model based on support vector machine (SVM).

A method based on wavelet transform in combination with support vector machine (SVM) is proposed for localizing text region.

A new fitting method for magnetic curve based on support vector machine in transformer emulation is presented. The method is applied.

A structural damage identification method based on the support vector machine and the particle swarm algorithm was proposed.

This paper sets up a new Support Vector Machine-Gussian Mixture Model(SVM-GMM) to improve speaker recognition rate based on open-set.

The support vector machine (SVM) is a new pattern recognition technology based on the statistical learning theory.

An approach for genotyping of STR locus based on ultraviolet(UV) spectroscopy and support vector machine(SVM) was studied.

A novel prediction model based on Least Squares Support Vector Machine (LS-SVM) with application in the milling area was proposed.

A method for fatalness assessment of flight safety hidden danger, based on support vector machine(SVM), was proposed.

For the problem of automatic vehicle recognition, a recognition method is proposed based on EMD and support vector machine.

Relevance feedback algorithm based on support vector machine and rough set for image retrieval is approached.

A novel model based on wavelet transform and support vector machine for dam deformation prediction is presented.

When the number of the training set is very large, the training time and needed memory of support vector machine increase quickly.

According to extracted features, one support vector machine is constructed for one pattern.

In this paper, a forecast of the new model of inter-bank offered rate based on support vector machine model was made.

A runoff prediction model was developed based on the multiple quantity index of SVM(support vector machine)method.

This paper proposes a thenar palmprint classification method based on Support Vector Machine(SVM).

In the character recognition module, a recognition approach based on support vector machine is applied.

Support Vector Machine (SVM) is a new data based modeling method based on statistical learning theory (SLT).

An audio steganalysis method for information detecting based on support vector machine is given.

This paper presented a traffic sign recognition algorithm based on SVM(support vector machine).

A learning machine based on support vector machine is proposed in this paper, which is applied to single-chip smart sensor system.

An adaptive inverse control method based on Least Squares support vector machine(LS-SVM) is studied in this paper.

The support vector machine(SVM) is a linear classification machine, it is used commonly in the pattern recognition and nonlinear regression.

and performing identification based on a support vector machine.

A new time series prediction method was put forward, based on fuzzy least square support vector machine (FLS-SVM).

The support vector machine (SVM) is a new learning machine based on the statistical learning theory.

A laser welding quality monitoring method is proposed, based on support vector machine.

According to the analysis of the support vector machine theory, an improved SVM is presented based on one of quasi-Newton algorithms (DFP).

A method of rural electricity consumption demand forecasting based on support vector machine has been proposed.

The step of classification based on directed acyclic graph support vector machine.

Application of theory of support vector machine for forecasting link travel time is discussed.

Thus it can be seen, carries on the forecast prospect using the support vector machine to the stock market extremely to favor.

In order to verify the support vector machine for predicting the experience of timber stands of timber species was feasible.

A soft sensing modeling method based on Niche Genetic Algorithm-Least Square Support Vector Machine (NGA-LSSVM) is proposed.

Support Vector Machine (SVM) is a novel powerful machine learning method based on SLT.

A new method of dynamic clustering based on the idea of optimal hypersphere and support vector machine.

A new method for density estimation was developed based on the Support Vector Machine(SVM).

A method for signal filtering based on support vector machine (SVM) was proposed.

In addition, we combined SVM with rough set theory, and got rough support vector machine algorithm (RSVM).

The anomaly detection method based on registry accesses using One Class Surport Vector Machine.

Even for efficient algorithms such as Support Vector Machine, large-scale problems are still tough.

An approach based on Support Vector Machine(SVM) is presented in this paper.

Support Vector Machine in the field of data mining has become a hot one.

By using the C4. 5 and the support vector machine, the improved algorithm proposed in this paper achieved a higher recognition rate.

Support vector machine is a new learning machine, and it is based on the statistics learning theory.

A method based on one-against-one-algorithm multi-class classification support vector machine was proposed.

A new data fusion method based on one-class Support Vector Machine (SVM) was proposed for candidate gene prioritization.

Therefore it is of great significance to study the properties of kernel function of support vector machine.

Therefore, it is important to study the kernel function and fuzzy recognition technology based on support vector machine.

Study of Active Learning Support Vector Machine and Its Application on Mongolian Text Classification

A support vector machine with a hybrid kernel and its application in underwater target recognition

A Study of the Modeling of a Boiler Superheating System Based on a Supportive Vector Machine

Application of a hybrid method in process monitor with independent component analysis and support vector machine

Support vector machine applied to the relationship between the content of some trace elements in hair and hypertension disease

Research in Support Vector Machine And Its Application in Quickly Nondestructive Inspection of Agricultural Product

A Study of Personal Credit Scoring Models on Support Vector Machine with Optimal Choice of Kernel Function Parameters

Support vector machine and mechanism model hybrid modeling method and its application to polyester production process

Application of the least square support vector machine in recognition of small samples

The Support Vector Machine Method and Its Elementary Applications to Synthetic Earthquake Prediction

Linear Programming Support Vector Machine and Its Application in Underwater Target Recognition

A New Method of Wavelet and Support Vector Machine for Detection of the Train Wheel Bruise

Study of Support Vector Machine Classification of Model of Toxicity Action of Organic Compounds

Study of support vector machine and its improved algorithms

Support Vector Machine and Its Application in Enhanced Oil Recovery Potentiality Prediction

Research of the Identification of Diamond Dresser Blunt Using Wavelet Packet Decomposition and Support Vector Machine

Support Vector Machine with Scaling Kernel and Its Application in Dynamic System Identification

Support Vector Machine and Its Application in Automatic Document Classification

Support Vector Machine Classification and Its Application for Equipment Condition Evaluation

deep well; drill stem failure; support vector machine; clustering analysis; failure reasons; precautionary measures;

Support Vector Machine Technique Applied to Computerized Prediction of Intermediate Phases of Some Phase Diagrams of Molten Salt Systems

Application of principal component analysis and support vector machine in evaluating corrosion severity of reinforcing steel in concrete

Freeway; Automatic Incident Detection; Factor Analysis; Support Vector Machine; Traffic Variable;

Digital modulation classification using probability density estimation and support vector machine

Support vector machine applied to detection of explosives for aviation security examination

Support Vector Machine and its Application in the Syndrome Diagnosis of Traditional Chinese Medicine

Review on support vector machine and its applications in petroleum exploration and development

Determination of the Artificial Bezoar Powder in Bezoar Powder by Near-Infrared Spectrometry and Support Vector Machine

Confidence Support Vector Machine Based on Algorithmic Theory of Randomness and its Application on Signature Verification

Improvement classification performance by the support vector machine ensemble

The relation between weighted least squares support vector machine and the least square problem

Study of telecom customer arrear evaluation based support vector machine

New support vector machine based classification algorithm and its application

Classification using a novel support vector machine fuzzy network for digital modulations in satellite communication

Application of hierarchical clustering support vector machine in turbogenerator fault diagnosis

Penalty function and its improved algorithms for regression type support vector machine

fuel cell ; hybrid modeling ; Proton Exchange Membrane Fuel Cell PEMFC ; Support Vector Machine SVM ; pressure-incremental model

Prediction of Eukaryotic Protein Subcellular Location Using a Novel Feature Extraction Method and Support Vector Machine

Support Vector Machine and Its Application in Gesture Recognition for Online Sketch Editing

Applicational study of support vector machine theory for machinery condition prediction

An Improved Sequential Minimization Optimization Algorithm for Support Vector Machine Training

Support Vector Machine-based Trajectory Recognition with Applications in the Adjustment of Radar Trajectory Prediction

An Improved Sequential Minimal Optimization Learning Algorithm for Regression Support Vector Machine

SAR image ; azimuth estimation ; support vector machine for regression ; feature extraction ; shadow

Influence analysis and self-adaptive optimization of support vector machine time series forecasting model parameters

Support vector machine for predicting apoptosis proteins types by incorporating protein instability index

An Incremental Learning Algorithm for Support Vector Machine and its Application

Application of Support Vector Machine Method in Soft Measurement of Kappa Number of Kraft Pulping Process

Support vector machine applied to the pattern recognition of activity of antagonists

then mutually high-order independent ICA features are used to train a support vector machine classifier;

Support Vector Machine and Its Applications to Function Approximation

Support vector machine applied to intelligent database of phase diagrams of molten salt systems

Support Vector Machine and Its Application in Foundation Engineering

Estimation of illumination chromaticity via adaptive reduced relevance vector machine

Maximum Entropy Approach for Generalized Support Vector Machine Optimization Problems

Support Vector Machine and Its Application in Natural Language Processing

An Incremental Parallel Training Algorithm with Multiple Support Vector Machine Classifiers

Research on incremental learning algorithm with multiple support vector machine classifiers

Equipment condition recognition with multi-category support vector machine in wireless sensor networks

The Application of the Support Vector Machine in Infared Imaging Automatic Target Recognition

An Adaptive Watermarking Scheme Utilizing Support Vector Machine for Synchronization

Support Vector Machine and Chaos-genetic Optimization Based Ultrasonic Flaw Identification

Weighted Support Vector Machine for Operation Monitoring of Wastewater Treatment Processes

Machinery Trend Condition Support Vector Machine Intelligent Prediction

Application of support vector machine in assessing contamination condition of high voltage insulators

Parameters optimization of hydro-mechanical deep drawing with orthogonal design and support vector machine

Study and application of genetic-support vector machine for nonlinear displacement time series forecasting

Extraction of Two-Dimensional Eye Position Data Using Support Vector Machine

Optimization of processing parameters of SiAlON - corundum castable with support vector machine

Comparison in Generalization Performance of Support Vector Machine Algorithms

Support Vector Machine and its Applications in Pattern Recognition

Support vector machine and kernel function characteristic analysis in pattern recognition

Support Vector Machine and Its Application to Machinery Fault Diagnosis

Support vector machine applied to chemistry and chemical technology

Application of Support Vector Machine in Steady State Fault Detection and Diagnosis of Liquid-propellant Rocket Engine

Simple Support Vector Machine Incorporating Invariance Features

Support Vector Machine for Spatial Feature Extraction and Classification of Remotely Sensed Imagery

High Dimensional Multispectral Data Classification by Support Vector Machine

Hybrid optimization algorithms of support vector machine ensembles and feature selection

The Support Vector Machine Algorithm Applied to Identification of Water-Flooded Zone with Well Logging

Application of support vector machine to apple classification with near-infrared spectroscopy

Incremental and Online Learning Algorithm for Regression Least Squares Support Vector Machine

Weighted Support Vector Machine Based Classification Algorithm for Uneven Class Size Problems

Support Vector Machine Applied to Metallurgy and Materials Science

Localized Proximal Support Vector Machine via Generalized Eigenvalues

The Adoptation of Phase Synchronization of EEG Recordings and Support Vector Machine for Recognition of Mental Tasks

Recognition of Nonlinear Fluorescence Spectrum of Support Vector Machine Networks

Support Vector Machine Based Unknown Nonlinear Systems Identification and Control

Data Mining; Decision Support; Support Vector Machine; Quantum Genetic Algorithm;

An Improved Least Squares Support Vector Machine and Its Applications

On-line support vector machine training algorithm and its application

Application of Time-Frequency Analysis and Support Vector Machine to on the Fault Diagnosis for Diesel Valve Train

Edge-effect Training for Fuzzy Support Vector Machine and its application

Genetic-algorithm-based support vector machine and its application in ERP

Support Vector Machine Method and Its Application to Prediction of Runoff

Detecting biomarkers from serum in nephroblastoma patients with support vector machine

Support Vector Machine Multi-class classification Based on an Improved Cross Validation Algorithm

Application of Support Vector Machine to Prediction of Refractive Index for High Molecular Weight Polymers