Background: In view of the low accuracy prognosis model esophageal squamous cell carcinoma (ESCC), this study aimed to optimize least squares support vector machine (LSSVM) algorithm determine uncertain prognostic factors using a Cloud model, and consequently, establish new high-precision ESCC.

Aiming at the parameter optimization of least square support vector machine (LS-SVM), an improved quantum-behaved particle swarm optimization (IQPSO) algorithm for LS-SVM parameter selection was proposed. Based on QPSO, the algorithm optimizes particle initializing positions and improves solving speed and precision by sampling and linearizing methods. IQPSO LSSVM model was test by test function...

Abstract: In this paper a new algorithm to identify Auto-Regressive Exogenous Models (ARX) based on Twin Support Vector Machine Regression (TSVR) has been developed. The model is determined by minimizing two ε insensitive loss functions. One of them determines the ε1-insensitive down bound regressor while the other determines the ε2-insensitive up-bound regressor. The algorithm is compared to S...

In this paper, a mutation strategy that is based on Lévy Probabily Distribution is introduced in Artificial Bee Colony algorithm. The purpose is to better exploit promising solutions found by the bees. Such an approach is used to improve the performance of the original ABC in optimizing Least Squares Support Vector Machine hyper parameters. From the conducted experiment, the proposed lvABC show...

Support Vector Machine(SVM) is a powerful classifier used successfully in many pattern recognition problems. Furthermore, the good performance of SVM classifier has been shown in handwriting recognition field. Least Squares SVM, like SVM, is based on the marginmaximization principle performing structural risk, but its training is easier: it is only needed to solve a convex linear problem rather...

Abstract A detailed understanding of the drilling fluid rheology and filtration properties is essential to assuring reduced loss during transport process. As per literature review, silica nanoparticle an exceptional additive enhance enhancement. However, a correlation based on nano-SiO 2 -water-based that can quantify nanofluids not available. Thus, two data-driven machine learning approaches a...