To alleviate the negative effects of air pollution, this paper explores a mixed prediction model pollutant concentration based on machine learning method. Firstly, in order to improve performance sparrow search algorithm least square support vector (SSA-LSSVM), reverse strategy-lens principle is introduced, and better solution obtained by optimizing current at same time. Secondly, according non...

Prediction and parameter optimization are effective methods for mine personnel to control blast-induced ground vibration. However, the challenge of prediction lies in multi-factor multi-effect nature open-pit blasting. This study proposes a hybrid intelligent model predict vibrations using least-squares support vector machine (LSSVM) optimized by particle swarm algorithm (PSO). Meanwhile, multi...

The deformation of landslides is a non-linear dynamic and complex process due to the impacts both inherent external factors. Understanding basis landslide essential prevent damage properties losses life. To forecast displacement, hybrid machine learning model proposed, in which Variational Modal Decomposition (VMD) implemented decompose measured total surface displacement into trend periodic co...

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...

In order to effectively solve the problems of low prediction accuracy and calculation efficiency existing methods for estimating economic loss in a subway station engineering project due rainstorm flooding, new intelligent model is developed using sparrow search algorithm (SSA), least-squares support vector machine (LSSVM) mean impact value (MIV) method. First, this study, 11 input variables ar...

Precise estimation of groundwater level (GWL) might be great importance for attaining sustainable development goals and integrated water resources management. Compared with alternative numerical models, soft computing methods are promising tools GWL prediction, which need more hydrogeological aquifer characteristics. The central aim this research is to explore the performance such well-accepted...

Nanopositioning technology is widely used in high-resolution applications. It often uses piezoelectric actuators due to their superior characteristics. However, exhibit a hysteresis phenomenon that limits positioning accuracy. To compensate for the effect, developing an accurate model of very important. This task challenging, requiring some considerations multivalued mapping loops and generaliz...