Climate change has an unprecedented impact on the world, and it is also important era proposition to be solved in China's development. Carbon emissions trading occupies position, which aims adapt global carbon neutrality context implement sustainable development requirements. The market mechanism of China deal with climate change, position. Based emission price data Guangdong Province from 2015...

Accurate real-time crash risk evaluation is essential for making prevention strategy in order to proactively improve traffic safety. Quite a number of models have been developed to evaluate traffic crash risk, by using real-time surveillance data. In this paper, the basic idea of traffic safety region is introduced into highway crash risk evaluation. Traffic safety region aims to describe the s...

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...

Abstract Monthly runoff forecasting has always been a key problem in water resources management. As data-driven method, the least square support vector machine (LSSVM) method investigated by numerous studies forecasting. However, selecting appropriate parameters for LSSVM is to obtaining satisfactory model performance. In this study, we propose hybrid monthly forecasting, VMD-SSA-LSSVM short, w...

Learning from positive and unlabeled examples (PU learning) is a special case of semi-supervised binary classification. The key feature of PU learning is that there is no labeled negative training data, which makes the traditional classification techniques inapplicable. Similar to the idea of Biased-SVM which is one of the most famous classifier, a biased least squares support vector machine cl...

Hybrid linear analysis (HLA), partial least-squares (PLS) regression, and the linear least square support vector machine (LSSVM) were used to determinate the soluble solids content (SSC) of apple by Fourier transform near-infrared (FT-NIR) spectroscopy. The performance of these three linear regression methods was compared. Results showed that HLA could be used for the analysis of complex solid ...

Problem statement: As the performance of Least Squares Support Vector Machines (LSSVM) is highly rely on its value of regularization parameter, γ and kernel parameter, σ, manmade approach is clearly not an appropriate solution since it may lead to blindness in certain extent. In addition, this technique is time consuming and unsystematic, which consequently affect the generalization performance...

Accurate prediction of forthcoming oxygen concentration during waterless live fish transportation plays a key role in reducing the abnormal occurrence, increasing the survival rate in delivery operations, and optimizing manufacturing costs. The most effective ambient monitoring techniques that are based on the analysis of historical process data when performing forecasting operations do not ful...