Search Results - last square support vector regression algorithm

Forecasting electricity consumption: A comparison of regression analysis, neural networks and least squares support vector machines by Kaytez, Fazil, Taplamacioglu, M. Cengiz, Cam, Ertugrul, Hardalac, Firat

“… Support vector machines (SVMs) and least squares support vector machines (LS-SVMs) are new techniques being adopted for energy consumption forecasting…”
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A grey seasonal least square support vector regression model for time series forecasting by Zhou, Weijie, Cheng, Yuke, Ding, Song, Chen, Li, Li, Ruojin

“… In this article, we propose a grey seasonal least square support vector regression, abbreviated as GSLSSVR, by combining the dummy variables, framework of the LSSVR model, and grey accumulation…”
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Developing a dengue forecast model using machine learning: A case study in China by Guo, Pi, Liu, Tao, Zhang, Qin, Wang, Li, Xiao, Jianpeng, Zhang, Qingying, Luo, Ganfeng, Li, Zhihao, He, Jianfeng, Zhang, Yonghui, Ma, Wenjun

“… Several machine learning algorithms, including the support vector regression (SVR) algorithm, step-down linear regression model, gradient boosted regression…”
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A hybrid super ensemble learning model for the early-stage prediction of diabetes risk by Doğru, Ayşe, Buyrukoğlu, Selim, Arı, Murat

“…) and a meta learner (support vector machines) as a result of a case…”
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Short-Term Demand Prediction Method for Online Car-Hailing Services Based on a Least Squares Support Vector Machine by Jiang, Shan, Chen, Wentian, Li, Zhiheng, Yu, Haiyang

“… prediction for online car-hailing services based on clustering algorithms and regression algorithms…”
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An adaptive fuzzy predictive control of nonlinear processes based on Multi-Kernel least squares support vector regression by Boulkaibet, I., Belarbi, K., Bououden, S., Chadli, M., Marwala, T.

“…–Sugeno system based Multi-Kernel Least Squares Support Vector Regression (TS-LSSVR). The proposed adaptive TS-LSSVR strategy is constructed using a multi-kernel least…”
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New model for prediction binary mixture of antihistamine decongestant using artificial neural networks and least squares support vector machine by spectrophotometry method by Mofavvaz, Shirin, Sohrabi, Mahmoud Reza, Nezamzadeh-Ejhieh, Alireza

“…In the present study, artificial neural networks (ANNs) and least squares support vector machines (LS-SVM…”
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A Hybrid Forecasting System Based on Comprehensive Feature Selection and Intelligent Optimization for Stock Price Index Forecasting by He, Xuecheng, Wang, Jujie

“… First, a recursive feature elimination with a cross-validation (RFECV) algorithm is designed to filter variables that have a significant impact on the target data from multiple datasets…”
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Estimating the Wear Rate of Diamond Cutting Wire Bead in Building Stone Cutting Using SVR and GA_MLP System by Babajan, Omid Jami, Bagherpour, Raheb

“…As the cutting stone is a wear process, performing this process with diamond pieces' aid can be considered the wear of stone particles bypassing diamond grains…”
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Comparison of machine learning techniques and spatial distribution of daily reference evapotranspiration in Türkiye by Yildirim, Demet, Küçüktopcu, Erdem, Cemek, Bilal, Simsek, Halis

“… This study investigated the feasibility and effectiveness of three ML techniques, including the k -nearest neighbor algorithm, multigene genetic programming, and support vector regression (SVR…”
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Predict Seasonal Maximum Freezing Depth Changes Using Machine Learning in China over the Last 50 Years by Wang, Shuo, Sheng, Yu, Ran, Youhua, Wang, Bingquan, Cao, Wei, Peng, Erxing, Peng, Chenyang

“… In this study, we evaluated the annual changes in seasonal maximum freezing depth (MFD) over China from 1971 to 2020 using an ensemble-modeling method based on support vector machine regression (SVMR…”
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A new short-term prediction method for estimation of the evaporation duct height by Mai, Y.B., Sheng, Z., Shi, H.Q., Li, C. L., Liao, Q.X., Bao, J.

“…) quickly and accurately. After that, the DEA, the support vector regression…”
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Development and Comparison of Regression Models for Determination of Starch in Chickpea Using NIR Spectroscopy by Priyadarshi, Madhu Bala

“… Over the last several decades, NIR spectroscopy's advent and broad application have been an enormous success story in analytical technology development…”
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Rapid Determination of Holocellulose and Lignin in Wood by Near Infrared Spectroscopy and Kernel Extreme Learning Machine by Yang, Hao, Liu, Yaoyao, Xiong, Zhixin, Liang, Long

“…To improve the production efficiency in the pulp and paper industry, the chemical composition of pulp wood species has to be measured in real-time, especially…”
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The generalized LASSO by Roth, V.

“…In the last few years, the support vector machine (SVM) method has motivated new interest in kernel regression techniques…”
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Modeling Bidirectional Polarization Distribution Function of Land Surfaces Using Machine Learning Techniques by Liu, Siyuan, Lin, Yi, Yan, Lei, Yang, Bin

“… In this study, three widely used ML algorithms—i.e., support vector regression (SVR), K-nearest…”
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Application of near‐infrared spectroscopy combined with chemometrics for online monitoring of Moluodan extraction by Tao, Lingyan, Li, Wenjing, Jin, Ye, Yang, Yue, Wu, Yongjiang, Liu, Xuesong

“… Particle swarm optimization–based least square support vector machines (PSO‐LS‐SVM) and partial least squares models were both established for quantitative analysis to determine the content of paeoniflorin online…”
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Comparative Assessment to Predict and Forecast Water-Cooled Chiller Power Consumption Using Machine Learning and Deep Learning Algorithms by Chaerun Nisa, Elsa, Kuan, Yean-Der

“…Over the last few decades, total energy consumption has increased while energy resources remain limited…”
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Mapping Coastal vulnerability using machine learning algorithms: A case study at North coastline of Sebou estuary, Morocco by Ennouali, Zhour, Fannassi, Youssef, Lahssini, Ghizlane, Benmohammadi, Aicha, Masria, Ali

“…+) during the last 19 years. Moreover, the rates of shoreline change were extracted by integrating ArcGIS and DSAS…”
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Application of Improved Least Squares Support Vector Machine in the Forecast of Daily Water Consumption by Zhang, Weiping, Yang, Qin, Kumar, Mohit, Mao, Yihua

“… consumption after noise reduction as output. In addition, we adopt the multiple scale chaos genetic with strong global search capability and faster search speed to optimize the parameters of least square support vector machine…”
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