Neural Support Vector Network
PREDICTION OF PLASMA PROTEIN BINDING AFFINITY BY SUPPORT VECTOR MACHINE AND ARTIFICIAL NEURAL NETWORK
... In nprtool data is divided into a 3 parts. Ist part is training. Second part is validation. Third part is testing data. In training part 70% data treat as training data. Out of 200 drugs 140 drugs is selected for ...
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Analysis of Ammonia Nitrogen Content in Water Based on Weighted Least Squares Support Vector Machine (WLSSVM) Algorithm
... squares support vector machine algo- ...squares support vector machine algorithm increases the weight para- meter setting, improves the speed and accuracy of prediction learning, and improves ...
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Title: A Study of Image Processing in Agriculture for Detect the Plant Diseases
... Abstract- Agricultural Image Processing is one of the core application of Image processing is one of the most growing research area that is having its participation in different application areas including the biometric ...
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An implementation of least square support vector machine (LS-SVM) for rehabilitation bio-signal analysis using surface electromyography (SEMG) signal
... xi LIST OF ABBREVIATIONS LS-SVM - Least Square Support Vector Machine SVM - Support Vector Machine k-NN - K nearest Neighbour ANN - Artificial Neural Network RBF Radial Basis Function LB[r] ...
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Machine learning approach for detection of nonTor traffic
... Tor network is popular in providing privacy and security to end user by anonymising the identity of internet users connecting through a series of tunnels and ...Artificial Neural Network and ...
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IJCSMC, Vol. 5, Issue. 5, May 2016, pg.483 – 488 A Survey on Classification Techniques in Data Mining for Analyzing Liver Disease Disorder
... The study surveyed some data mining techniques to predict the liver disease at earlier stage. The study analyzed algorithms such as C4.5, Naive Bayes, Decision Tree, Support Vector Machine, Back Propagation ...
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Support Vector Regression Integrated with Fruit Fly Optimization Algorithm for River Flow Forecasting in Lake Urmia Basin
... Monthly river flow forecasting using artificial neural network and support vector regression models. 316[r] ...
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Performance comparison of three artificial neural network methods for classification of electroencephalograph signals of five mental tasks
... of neural network with resilient back propagation training method, support vector machine and radial bases function Neural Net- work for classifying of mental tasks ...Function) ...
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Disease Identification in Cotton Plants Using Spatial FCM & PNN Classifier
... on support vector machines [4] for developing weather based prediction models of plant diseases is proposed by Rakesh & ...artificial neural network (back propagation neural ...
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Speech emotion classification using SVM and MLP on prosodic and voice quality features
... the Support Vector Machine (SVM) and the Multi-Layer Perceptron (MLP) Neural Network, using prosodic and voice quality features extracted from the Berlin Emotional Database, is ...
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Machine learning approach for detection of non-Tor Traffic
... Tor network is popular in providing privacy and security to end user by anonymizing the identity of internet users connecting through a series of tunnels and ...Tor Network Traffic dataset and ...
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Electroencephalography Analysis Using Neural Network and Support Vector Machine during Sleep
... Based on the pattern recognition, the analysis algo- rithm for sleep stage undergoes a signal processing of obtained EEG signal data and selects the parameter for the frequency domain which well indicates the sleep ...
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Soft Computing Techniques Based Automatic Licence Plate Recognition Systems for Indian Vehicles
... Abstract: Automobile industries are growing exponentially in last decade in India. Growth in the vehicle numbers results in much more road accidents and traffic management problem. Not only this, long queues at toll ...
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Deep Learning For Anticipation Of Cardiovascular Disease: A Practical Approach
... proposes Support Vector Machine (SVM), Artificial Neural Network (ANN) Multilayer Perceptron, (Recurrent Neural Network – Long Short Term Memory (RNN- LSTM) and Independent RNN ...
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Support Vector Regression and Artificial Neural Network Approaches: Case of Economic Growth in East Africa Community
... [12] Molinet, T., J. A. Molinet, M. E. Betancourt, A. Palmer, J. J. Montaño (2015). “Models of Artificial Neural Networks Applied to Demand Forecasting in Nonconsolidated Tourist Destinations”. Methodology: ...
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Applying ANN, ANFIS, and LSSVM Models for Estimation of Acid Solvent Solubility in Supercritical CO
... artificial neural network, Multi-layer Perceptron artificial neural network, Least squares support vector machine and adaptive neuro-fuzzy inference system are developed to ...
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Knowledge Discovery and Diseases Prediction: A Comparative Study of Machine Learning Techniques
... decision support systems for disease classification through a set of medical ...techniques. Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Neural Network (NN), Adaptive ...
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An Ensemble Classification Approach for Intrusion Detection
... Increased cyber attacks in various forms compel everyone to implement effective intrusion detection systems for protecting their information wealth. From last two decades, there has been extensive research going on in ...
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Application research of convolution neural network in image classification of icing monitoring in power grid
... convolution neural network, this paper applies it to the detection of power network ...power network icing detection image based on convolution neural network is proposed, which ...
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A Fuzzy Based Classification – An Experimental Analysis
... weight vector and biased term that are fuzzy ...fuzzy Support Vector Machine and Fuzzy Neural Network may be very useful in classifying biological ...
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