This paper parallelizes the spatial pyramid match kernel (SPK) implementation. SPK is one of the most usable kernel methods, along with support vector machine classifier, with high accuracy in object recognition. MATLAB parallel computing toolbox has been used to parallelize SPK. In this implementation, MATLAB Message Passing Interface (MPI) functions and features included in the toolbox help u...

Permeability prediction problem has been examined using several methods such as empirical formulas, regression analysis and intelligent systems especially neural networks and fuzzy logic. This study proposes an improved and novel model for predicting permeability from conventional well log data. The methodology is integration of empirical formulas, multiple regression and neuro-fuzzy in a commi...

According to the fact that parameter selection of support vector machine(SVM) for fault diagnosis is difficult, a new method based on bacterial foraging algorithm(BAF) for support vector machine parameter optimization was proposed , then the faster optimization of the parameters C and RBF kernel parameter γ was performed. The crack rotor as the experiment object, firstly, AE signal of rotors wi...

When the standard genetic algorithm is used to solve the fuzzy programming problem, poor convergence occurs. In order to overcome this defect, this paper presents a hybrid intelligent evolutionary algorithm based on nonlinear support vector machine (SVM) to solve the fuzzy programming problem. Firstly, based on the research of genetic algorithm, evolutionary strategy and genetic algorithm are c...

In order to improve the efficiency and classification ability of Support vector machines (SVM) based on stochastic gradient descent algorithm, three algorithms of improved stochastic gradient descent (SGD) are used to solve support vector machine, which are Momentum, Nesterov accelerated gradient (NAG), RMSprop. The experimental results show that the algorithm based on RMSprop for solving the l...

Abstract In this paper, a deep learning RNN model is used to classify Tibetan texts. The core idea first preprocess the news corpus, and then use syllables construct syllable table based on lexical grammatical structure of Tibetan, embed in sentence, represent each as fixed Numerical vector. Secondly, cyclic neural network constructed. First, text different lengths filled or truncated into sequ...

Abstract The author proposes a model evaluation based on the GA-SVM to better understand of company’s relationship and core competitiveness. system index is reduced by relative gray analysis, support vector machine optimized genetic algorithm, specific algorithm steps are introduced. Select models from top 100 enterprises in China’s construction industry 2020 published China Construction Indust...

This paper proposes to use a fuzzy entropy based feature selection approach to reduce the dimensionality of DAIS hyperspectral data. To compare its performance, three other filter based feature selection approaches were used. A support vector machine was used as a classification algorithm. In order to compare various feature selection approaches with full dataset, McNemar’s test based test for ...

Multivariate data analysis techniques have the potential to improve physics analyses in many ways. The common classification problem of signal/background discrimination is one example. A comparison of a conventional method and a Support Vector Machine algorithm is presented here for the case of identifying top quark signal events in the dilepton decay channel amidst a large number of background...