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.

In the application of regression prediction through big data technology, error between predicted value and true is often large. order to reduce prediction, this paper proposes an Intelligent Data Prediction (IDP) scheme for Smart Service. It uses Least Squares Support Vector Machine (LSSVM) as basic model. Since there no standard procedure determining main parameters LSSVM, improved Particle Sw...

A reliability analysis method based on least squares support vector machines with an improved particle swarm optimization algorithm (IPSO-LSSVM) is proposed to calculate the of concrete gravity dams when explicit nonlinear limit-state functions are difficult obtain accurately. First, main failure modes and their influencing factors determined. Second, Latin hypercube sampling used create sample...

In order to improve the performance of voltage source converter-high voltage direct current (VSC-HVDC) system, we propose an improved auto-disturbance rejection control (ADRC) method based on least squares support vector machines (LSSVM) in the rectifier side. Firstly, we deduce the high frequency transient mathematical model of VSC-HVDC system. Then we investigate the ADRC and LSSVM principles...

One of the challenging problems in the Oil & Gas industry is accurate and reliable multiphase flow rate measurement in a three-phase flow. Application of methods with minimized uncertainty is required in the industry. Previous developed correlations for two-phase flow are complex and not capable of three-phase flow. Hence phase behavior identification in different conditions to designing and mo...

Electricity price and load forecasting are two important problems for market participants and independent system operators (ISO) in smart grid environments. Most existing papers predict price and load separately, while, the aggregate reaction of consumers can potentially shift the demand curve in the market, resulting in prices that may differ from the initial forecasts. In this regards, demand...

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...

We conduct an empirical analysis to investigate the relationship between thirty seven different source code metrics with fifteen different Web Service QoS (Quality of Service) parameters. The source code metrics used in our experiments consists of nineteen Object-Oriented metrics, six Baski and Misra metrics, and twelve Harry M. Sneed metrics. We apply Principal Component Analysis (PCA) and Rou...