Accurate identification of lithology is the basis and key process fine logging interpretation evaluation. However, reservoirs formed by different sedimentary environments tectonic movements generally have characteristics complex diverse strong heterogeneity, which brings great difficulty to reservoir lithology. This paper proposes an automatic technology for based on GWO-SVM algorithm model. Th...

Support Vector Machines (SVM) have been extensively studied and have shown remarkable success in many applications. However the success of SVM is very limited when it is applied to the problem of learning from imbalanced datasets in which negative instances heavily outnumber the positive instances (e.g. in gene profiling and detecting credit card fraud). This paper discusses the factors behind ...

Recently, Support Vector Machine (SVM) has become a very dynamic and popular topic in the Neural Network community for its abilities to perform classification, estimation, and regression. One of the major tasks in the SVM algorithm is to locate the points, or rather support vectors, based on which we construct the discriminant boundary in classification task. In the process of studying the meth...

Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on a financial exchange. The successful prediction of a stock's future price will maximize investor’s gains. This paper proposes a machine learning model to predict stock market price. The proposed algorithm integrates Particle swarm optimization (PSO) and least squ...

This paper describes our contribution to the English Entrance Exams task of CLEF 2015, which requires participating systems to automatically solve multiple choice reading comprehension tasks. We use a combination of text segmentation and different similarity measures with the aim of exploiting two observed aspects of tests: 1) the often linear relationship between reading text and test question...

The utilization of shared (P2P) applications is developing significantly, which brings about a few major issues, for example, the system clog and traffic obstruction. Consequently P2P traffic identification is the most blazing theme of P2P traffic administration. Support vector machine (SVM) has points of interest with settling little examples for P2P characterization issues. However, the execu...

Support vector machine (SVM) was used to analyze the occurrence of roach in Flemish stream basins (Belgium). Several habitat and physico?chemical variables were used as inputs for the model development. The biotic variable merely consisted of abundance data which was used for predicting presence/absence of roach. Genetic algorithm (GA) was combined with SVM in order to select the most important...

Loan default evaluation and discrimination is a complicated issue because of its nonlinearity and uncertainty. Least square support vector machine (LS-SVM) has been successfully employed to solve regression and time series problem. This paper proposes a novel PSO-LS-SVM model based on the improved PSO algorithm to optimize parameters of LS-SVM, which is a new improved form by synthesizing the e...