Pijush Samui

TL;DR: In this article, a multivariate adaptive regression spline (MARS) for determination of elastic modulus (Ej) of jointed rock mass is presented. But the results from the developed MARS model have been compared with those of artificial neural networks (ANNs) using average absolute error.

TL;DR: In this article, Support Vector Machine (SVM) and Relevance Vector Machine(RVM) were used for prediction of Evaporation Losses (E) in reservoirs.

TL;DR: In this article, a multivariate adaptive regression splines model (MARS) was used as a feature extraction method to extract the optimum inputs that use to design the high performance concrete (HPC) structures.

TL;DR: Four advanced computational frameworks including relevance vector machine (RVM), group method of data handling (GMDH), hybridization of adaptive neuro-fuzzy interface system (ANFIS) and biogeography-based optimisation (BBO) are proposed as novel approaches to predict the heating load (HL) and cooling load (CL) of residential buildings.

TL;DR: The study ascertains that the GRNN model was a qualified data-intelligent tool for temperature estimation without a need for climate-based inputs, at least in the present investigation, and this model can be explored for its utility in energy management, building and construction, agriculture, heatwave studies, health and other socio-economic areas, particularly in data-sparse regions.