With the development of renewable energy, energy incubators have emerged continuously. However, these present a crude model low-level replication and large-scale expansion, which has triggered series urgent problems including unbalanced regional development, low incubation efficiency, resource utilization, vicious competition for resources. There are huge challenges sustainable in future. A sci...

This paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (LSSVM). Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared to select an appropriate wavelet for feature extraction. The fault diagnosis method co...

Predicting the deformation of landslides is significant for landslide early warning. Taking Shuping in Three Gorges Reservoir area (TGRA) as a case, displacement decomposed into two components by time series model (TSM). The least squares support vector machine (LSSVM) optimized particle swarm optimization (PSO) selected to predict prediction based on rainfall and reservoir water level (RWL). F...

Soft sensor is an effective tool to estimate industrial process variables which are hard to be measured online for the technical or economical reasons. The modeling methods of the sensor are related to the approximating precision and speed. A soft sensor model with rough set and Least Squares Support Vector Machines (LSSVM) is presented in the paper. The rough set is employed to compress the da...

In this paper, a data-driven modeling technique is proposed for temperature forecasting. Due to the high dimensionality, LASSO is used as feature selection approach. Considering spatio-temporal structure of the weather dataset, first LASSO is applied in a spatial and temporal scenario, independently. Next, a feature is included in the model if it is selected by both. Finally, Least Squares Supp...

Support Vector Machine has appeared as an active study in machine learning community and extensively used in various fields including in prediction, pattern recognition and many more. However, the Least Squares Support Vector Machine which is a variant of Support Vector Machine offers better solution strategy. In order to utilize the LSSVM capability in data mining task such as prediction, ther...

A quantitative structure–property relationship (QSPR) study was performed for predicting the hydrophobicity of Pt(IV) complexes. Two four-parameter equations, one based solely on structural descriptors derived from electrostatic potentials (ESPs) molecular surface, and other integrated ESP with surface area (AS), were firstly constructed. Mechanistic interpretations introduced elucidated in ter...