A swarm intelligence-based machine learning approach for predicting soil shear strength for road construction: a case study at Trung Luong National Expressway Project (Vietnam)
Sign Up to like & getrecommendations! Published in 2018 at "Engineering with Computers"
DOI: 10.1007/s00366-018-0643-1
Abstract: Determining the shear strength of soil is an important task in the design phase of construction project. This study puts forward an artificial intelligence (AI) solution to estimate this parameter of soil. The proposed approach… read more here.
Keywords: project; construction; shear strength; lssvm ... See more keywords
Forecasting and uncertainty analysis of day-ahead photovoltaic power using a novel forecasting method
Sign Up to like & getrecommendations! Published in 2021 at "Applied Energy"
DOI: 10.1016/j.apenergy.2021.117291
Abstract: Abstract The primary means to promote grid-connected photovoltaic power generation is through accurately forecasting the power output from photovoltaic power stations. This paper proposes a method for day-ahead photovoltaic power forecasting (PPF) and uncertainty analysis… read more here.
Keywords: ahead photovoltaic; lssvm; power; photovoltaic power ... See more keywords
Daily PM2.5 concentration prediction based on principal component analysis and LSSVM optimized by cuckoo search algorithm.
Sign Up to like & getrecommendations! Published in 2017 at "Journal of environmental management"
DOI: 10.1016/j.jenvman.2016.12.011
Abstract: Increased attention has been paid to PM2.5 pollution in China. Due to its detrimental effects on environment and health, it is important to establish a PM2.5 concentration forecasting model with high precision for its monitoring… read more here.
Keywords: pm2 concentration; principal component; lssvm; model ... See more keywords
Prediction of the corrosion rates of subsea pipelines via KPCA
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-09685-6
Abstract: The development of a precise model for predicting pipeline corrosion rates is essential for ensuring the safe operation of pipelines. To address the issues of inadequate stability and prolonged execution time associated with traditional models,… read more here.
Keywords: subsea pipelines; lssvm; corrosion rates; prediction ... See more keywords
Remaining useful life prediction of lithium battery based on CEEMD-SE-IPSO-LSSVM hybrid model
Sign Up to like & getrecommendations! Published in 2024 at "International Journal of Low-Carbon Technologies"
DOI: 10.1093/ijlct/ctae120
Abstract: In order to prevent accidents caused by battery aging, accurately predicting the remaining useful life (RUL) is a critical and highly challenging task in battery management systems. This article describes a lithium-ion battery RUL prediction… read more here.
Keywords: battery; lssvm; hybrid model; prediction ... See more keywords
A Strategy for the Effective Optimization of Pharmaceutical Formulations Based on Parameter-Optimized Support Vector Machine Model
Sign Up to like & getrecommendations! Published in 2022 at "AAPS PharmSciTech"
DOI: 10.1208/s12249-022-02210-2
Abstract: Engineering pharmaceutical formulations is governed by a number of variables, and the finding of the optimal preparation is intricately linked to the exploration of a multiparametric space through a variety of optimization tasks. As a… read more here.
Keywords: lssvm; pharmaceutical formulations; optimization; model ... See more keywords
Fault diagnosis of nonlinear analog circuits using generalized frequency response function and LSSVM
Sign Up to like & getrecommendations! Published in 2024 at "PLOS ONE"
DOI: 10.1371/journal.pone.0316151
Abstract: A fault diagnosis method of nonlinear analog circuits is proposed that combines the generalized frequency response function (GFRF) and the simplified least squares support vector machine (LSSVM). In this study, the harmonic signal is used… read more here.
Keywords: lssvm; fault diagnosis; fault; nonlinear analog ... See more keywords
Prediction Model for Dissolved Gas Concentration in Transformer Oil Based on Modified Grey Wolf Optimizer and LSSVM with Grey Relational Analysis and Empirical Mode Decomposition
Sign Up to like & getrecommendations! Published in 2020 at "Energies"
DOI: 10.3390/en13020422
Abstract: Oil-immersed transformer is one of the most important components in the power system. The dissolved gas concentration prediction in oil is vital for early incipient fault detection of transformer. In this paper, a model for… read more here.
Keywords: dissolved gas; lssvm; oil; gas concentration ... See more keywords