In this paper, a hybrid particle swarm optimization based on the natural selection (NPSO) was presented and used to optimize the parameters of Least Square Support Vector Machine (LSSVM). The NPSO algorithm overcomes the shortcomings of premature convergence and poor local search capability of traditional Particle Swarm Optimization (PSO). Then a classification model of oil-gas-water three-phas...

Real-time and accurate short-term traffic flow prediction is the premise and key of intelligent traffic control and guidance system. According to this problem, this paper put forward a prediction model based on multivariable phase space reconstruction and least squares support vector machine (LSSVM). First, the model confirms embedding dimension and delay time of the traffic flow, occupancy and...

Shearers play an important role in fully mechanized coal mining face and accurately identifying their cutting pattern is very helpful for improving the automation level of shearers and ensuring the safety of coal mining. The least squares support vector machine (LSSVM) has been proven to offer strong potential in prediction and classification issues, particularly by employing an appropriate met...

In this study, a novel least square support vector machine (LSSVM) model integrated with gradient-based optimizer (GBO) algorithm is introduced for the assessment of water quality (WQ) parameters. For purpose, three stations, including Ahvaz, Armand, and Gotvand in Karun river basin, have been selected to electrical conductivity (EC) total dissolved solids (TDS). First, prove superiority LSSVM-...

The compressibility factor (Z-factor) of natural gases is necessary in many gas reservoir engineering calculations. Accurate determination of this parameter is of crucial need and challenges a large number of used simulators in petroleum engineering. Although numerous studies for prediction of gas compressibility factor have been reported in the literature, the accurate prediction of this param...

The paper investigates the relative influence of centroid three-phase squirrel cage induction motor rotor bar cross section, on breakdown (maximum) torque machine. angle taper, top width and radial depth as established design variables, were also investigated so to properly situate degree centroid, in comparison; far maximum is concerned. machines their steady state operating mode using equival...

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...

in this paper, we present a new brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (ls-svm). the method consists of three steps. in the first two steps, the skull is removed and cerebrospinal fluid (csf) is extracted. these two steps are performed using the fast toolbox (fmrib's a...