全部文献期刊会议图书|学者科研项目
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作者:Zhongfu Tan , Gejirifu De , Menglu Li ...
来源:[J].Journal of Cleaner Production(IF 3.398), 2020, Vol.248
摘要:... Secondly, with the help of the weight sharing mechanism in the multi-task learning and the idea of least square support vector machine, a combined forecasting model of electricity, heat, cooling and gas loads based on the multi-task learning and least square support vector machine...
作者:Xiaohui Yuan , Qingxiong Tan , Xiaohui Lei ...
来源:[J].Energy(IF 3.651), 2017, Vol.129, pp.122-137
摘要:... A hybrid autoregressive fractionally integrated moving average and least square support vector machine model is proposed to forecast short-term wind power. The proposed hybrid model takes advantage of the respective superiority of autoregressive fractionally integrated moving...
作者:Nastaran Khazali , Mohammad Sharifi
来源:[J].Journal of Petroleum Science and Engineering(IF 0.997), 2019, Vol.180, pp.62-77
摘要:... As an alternative approach, machine learning deals with large volumes of data (which are recorded in a long period of times) to find the relationship among the related variables (Liu and Horne, 2013a). Here, we aim to describe the usage of the least square support vector machine...
作者:Jin-peng Liu , Chang-ling Li
来源:[J].Sustainability, 2017, Vol.9 (7)
摘要:... To improve the forecasting accuracy, this paper proposes a load forecasting system based on wavelet least square support vector machine and sperm whale algorithm. Firstly, the methods of discrete wavelet transform and inconsistency rate model (DWT-IR) are used to select the o...
作者:Chuan Luo , Chi Huang , Jinde Cao ...
来源:[J].Neural Processing Letters(IF 1.24), 2019, Vol.50 (5), pp.2305-2322
摘要:... The least square support vector machine (LSSVM) has powerful capabilities for time series and nonlinear regression prediction problems if it can select appropriate parameters. To search the optimal parameters of LSSVM, this paper proposes a hybrid optimization algorithm which...
作者:Shuo Guo , Decheng Yuan , Ridong Zhang ...
来源:[J].Chemometrics and Intelligent Laboratory Systems(IF 2.291), 2016, Vol.158, pp.69-79
摘要:... In this paper, we present a novel machine learning method for predicting promoter. First, the function motifs in different regions of Human promoter sequences have been recognized using Gaussian Mixture Model (GMM). The optimum number of GMM is given by the fuzzy cluster reco...
作者:Siuly , Yan Li , Peng (Paul) Wen
来源:[J].Computer Methods and Programs in Biomedicine(IF 1.555), 2010, Vol.104 (3), pp.358-372
摘要:Abstract(#br)This paper presents a new approach called clustering technique-based least square support vector machine (CT-LS-SVM) for the classification of EEG signals. Decision making is performed in two stages. In the first stage, clustering technique (CT) has been used to extr...
作者:Wentong Cui , Xuefeng Yan
来源:[J].Chemometrics and Intelligent Laboratory Systems(IF 2.291), 2009, Vol.98 (2), pp.130-135
摘要:Abstract(#br)In order to eliminate the influence of unavoidable outliers in training sample on a model's performance, a novel least square support vector machine regression, which combines outlier detection approach and adaptive weight value for the training sample, is propos...
作者:Ravinesh C Deo , Ozgur Kisi , Vijay P Singh
来源:[J].Atmospheric Research(IF 2.2), 2017, Vol.184, pp.149-175
摘要:... This study advances drought modelling using multivariate adaptive regression splines (MARS), least square support vector machine (LSSVM), and M5Tree models by forecasting SPI in eastern Australia. MARS model incorporated rainfall as mandatory predictor with month (periodic...
作者:Salim Heddam , Ozgur Kisi
来源:[J].Journal of Hydrology(IF 2.964), 2018, Vol.559, pp.499-509
摘要:Abstract(#br)In the present study, three types of artificial intelligence techniques, least square support vector machine (LSSVM), multivariate adaptive regression splines (MARS) and M5 model tree (M5T) are applied for modeling daily dissolved oxygen (DO) concentration using ...

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