This research aims to estimate the overflow capacity of a curved labyrinth using different intelligent prediction models, namely adaptive neural-fuzzy inference system, support vector machine, M5 model tree, least-squares machine and machine–bat algorithm (LSSVM-BA). A total 355 empirical data for 6 congressional models were extracted from results laboratory study on models. The parameters upst...

Constitutive modeling of clay is an important research in geotechnical engineering. It is difficult to use precise mathematical expressions to approximate stress-strain relationship of clay. Artificial neural network (ANN) and support vector machine (SVM) have been successfully used in constitutive modeling of clay. However, generalization ability of ANN has some limitations, and application of...

To reduce the influence of random fluctuation on wind power prediction, a new ultra-short-term prediction model, based wavelet decomposition (WD), variational mode (VMD), and least-squares support vector machine (LSSVM), is proposed in this paper. The method double LSSVM, where sequence decomposed by WD into low- high-frequency components, which are further VMD to obtain many modal components w...

In recent years, with the deepening of China’s electricity sales side reform and electricity market opening up gradually, the forecasting of electricity consumption (FoEC) becomes an extremely important technique for the electricity market. At present, how to forecast the electricity accurately and make an evaluation of results scientifically are still key research topics. In this paper, we pro...

This paper proposed a gas emission prediction method based on feature selection and improved machine learning, as traditional models are neither accurate nor universally applicable. Through analysis, this identified 12 factors that affected emissions. A total of 30 groups typical data for outflow were standardized, after which full subset regression was used to categorize influencing into diffe...

In this paper, a mutation strategy that is based on Lévy Probabily Distribution is introduced in Artificial Bee Colony algorithm. The purpose is to better exploit promising solutions found by the bees. Such an approach is used to improve the performance of the original ABC in optimizing Least Squares Support Vector Machine hyper parameters. From the conducted experiment, the proposed lvABC show...

In this paper, we apply Sequential Unconstrained Minimization Techniques (SUMTs) to the classical formulations of both the classical L1 norm SVM and the least squares SVM. We show that each can be solved as a sequence of unconstrained optimization problems with only box constraints. We propose relaxed SVM and relaxed LSSVM formulations that correspond to a single problem in the corresponding up...