[PDF] Top 20 Nanomaterials Characterization Using Hybrid Genetic Algorithm Based Support Vector Machines
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Nanomaterials Characterization Using Hybrid Genetic Algorithm Based Support Vector Machines
... , and that a separate optimization of each parameter is not adequate enough to find the optimal regression model [16]. In view of the above, in the practical application of SVM regression, usually a time-consuming grid ... See full document
8
Design of a Novel Hybrid Algorithm for Improved Speech Recognition with Support Vector Machines Classifier
... are based on Mel-Frequency Cepstral Coefficients (MFCCs), Linear predictive Coding (LPCs), and prosodic ...feature vector dimensions and computational complexity are higher to a greater ...reduced ... See full document
6
PROPOSED MODELS OF ADAPTIVE KNOWLEDGE AGGREGATOR
... a hybrid method that uses a reliable machine learning technique known as support vector regression and a genetic algorithm was used with fuzzy possibilistic clustering to estimate ... See full document
6
New Intelligent Classification Techniques for Diagnosis of Diabetes Mellitus based on Modified PSO
... treatment. Hybrid optimization techniques are in the form Artificial Neural networks, Genetic Algorithm, Fuzzy classifier, Support Vector Machine, Least Squares Support ... See full document
7
A BIRD’S VIEW ON RELATED LITERATURE ON GENETIC ALGORITHM
... the hybrid system as an able device to dole out with construction engineering and management ...optimized hybrid artificial intelligence model to assimilate a fast messy genetic algorithm ... See full document
8
Detect Climatic Factors Contributing to Dengue Outbreak based on Wavelet, Support Vector Machines and Genetic Algorithm
... Among all vector-borne diseases, mosquito-borne ones are one of the greatest health threats in the world. It is estimated that about 50 to 100 million people have been infected by dengue virus, which is ... See full document
5
Feature Selection Based On Hybrid Genetic Algorithm With Support Vector Machine (GA-SVM)
... method based on ...which based on the best incremental ranked subset according to some measure of ...blanket-embedded genetic algorithm method, which based memetic operators add or ... See full document
9
Support Vector Machines Networks to Hybrid Neuro Genetic SVMs in Portfolio Selection
... problems. Support Vector Machine (SVM) use kernel Adatron algorithm in the Neuro Solutions software which was implemented to perform only classifications, without being able to approximate ... See full document
7
Characterization of digital medical images utilizing support vector machines
... estimation algorithm that separates data in two classes, but since all classification problems can be restricted to consideration of the two-class classification problem without loss of generality, SVMs can be ... See full document
9
Control and Modeling of Wind Turbines Using Genetic Algorithms and Support Vector Machines for Regression
... a hybrid approach based on the Support Vector machines (SVM) and genetic algorithms (GA) is ...learning machines that can perform binary classification and real value ... See full document
9
Support vector machines applied to the genetic classification problem of hybrid populations with high degrees of similarity
... the genetic classification of simulated hybrid ...97.5% genetic similarity, which is quite ...as Support Vector Machine (SVM) (Lorena et al., 2003). SVM is based on Statistical ... See full document
10
Deformation prediction model of surrounding rock based on GA LSSVM markov
... given based on Genetic Algorithm (GA), Least Square Support Vector Machines (LSSVM) and markov ...theory. Genetic algorithm is used to improve the para- meter of ... See full document
6
Online Full Text
... for support vector machines in a hybrid Data Mining and Case-Based Reasoning system which incorporates a vector model to help transfer textual information to numerical ... See full document
5
Clustering Via Supervised Support Vector Machines
... SVM-Relabeler algorithm does not use an objective function and the hope is that by running the algorithm in its purest form the resulting clusters are reliable ...this algorithm in this basic fashion ... See full document
93
Polynomial Smooth Twin Support Vector Machines Based on Invasive Weed Optimization Algorithm
... chunking algorithm [8], decomposition algorithm [9] and sequential minimal optimization (SMO) [10], ...algorithms based on standard ...proximal support vector machine ...twin ... See full document
8
Predicate based Algorithm for Malicious Web Page Detection using Genetic Fuzzy Systems and Support Vector Machine
... Web page requires largest security concern in the Internet. They are grouped to form a web site with numerous links and hyperlinks. Web pages may contain multimedia, images, videos and text. A web site is a collection of ... See full document
7
Consensus-Based Distributed Support Vector Machines
... train support vector machines when training data are distributed across different nodes, and their communication to a centralized processing unit is prohibited due to, for example, communication ... See full document
45
Hyperspectral Image Classification Based on Hierarchical SVM Algorithm for Improving Overall Accuracy
... and using hyperspectral image data, a hierarchical algorithm based on SVM is proposed in this ...SVM algorithm is accomplished on clusters with selected ...discriminated based on SVM ... See full document
11
The Diagnosis of Epilepsy by Gravitational Search Algorithm and Support Vector Machines
... Subasi et al.[2] applied an autoregressive (AR) model and neural network to classify EEG signals in order to diagnose the epilepsy seizure. Their experimental results show that the percentage of experimental data ... See full document
15
Sparse Deconvolution Using Support Vector Machines
... methods, using as impulse response a prototype obtained from the B-scan in a single line where clearly only one reflection was ...each algorithm were adjusted accordingly to the results obtained with the ... See full document
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