VECTOR ERROR CORRECTION MODEL FOR FORECASTING SHEEP NUMBERS IN BULGARIA by Tsvetana HARIZANOVA–METODIEVA, Hristina HARIZANOVA, Zornica STOYANOVA

“…The aim of this study was to forecast sheep numbers in Bulgaria on 01.11.2016 and on 01.11.2017, using a vector error correction model (VECM). A vector error correction model was constructed to forecast sheep numbers in Bulgaria for 2016 and 2017. …”
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Macroeconomic Determinants of Investment Decisions for Medium and Large Enterprises in Poland’s Manufacturing Sector by Adam Andrzej Zając, Michał Wielechowski, Krzysztof Smoleń, Dariusz Karaś

“…Cointegration analysis and the Vector Error Correction Model (VECM) are employed to identify macroeconomic indicators that consistently impact the propensity to invest in specific sectors, while also assessing the presence of investment seasonality. …”
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Research and Simulation of Metro Pantograph-catenary SystemBased on Least Square Support Vector Machine by Jiang Wei, Huang Yuping

“…A model of pantograph-catenary system based on the error correlation was put forward, and the least squares supportvector machine (LSSVM) method was used to study the parameters of the model. …”
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Deep Learning Shield Attitude Prediction Model Based on Grey Correlation Analysis by Ke MAN, Zongxu LIU, Yan SHANG, Zhifei SONG, Xiaoli LIU, Bao SU

“…Objective A stacking ensemble prediction model based on long short-term memory (LSTM) and support vector regression (SVR) is proposed to address the issue of shield attitude deviation from the tunnel design axis.Methods The grey correlation analysis was employed to remove the rolling angle parameters with low grey correlation and then denoise them using discrete wavelet transform (DWT). …”
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Blasting vibration velocity prediction of open pit mines based on GRA-EPSO-SVM model by Pengfei ZHANG, Yong YUAN, Yunhua HE, Shaojun DAI, Jiazhen LI, Xuehai CHI, Wei LI, Xue SUN, Jiao ZHANG, Runcai BAI, Honglu FEI

“…In the scene of coal and rock interbedded blasting in open-pit mine, aiming at the problems that the existing prediction methods of blasting vibration peak value are difficult to achieve ideal prediction results, resulting in unreasonable design of blasting parameters and initiation network, a prediction model of blasting vibration peak value based on integrated particle swarm optimization support vector machine algorithm (GRA-EPSO-SVM) with grey correlation degree feature selection is proposed. …”
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Support Vector Regression and Beta Distribution for the Modeling of Incumbent Party vote for Presidential Elections by R., Kikawa, M, N. Ngungu, D., Ntirampeba, A., Ssematimba

“…Due to the forecasting aspect, model performance is focused on mainly one goodness-of-fit measure, that is, the prediction error rather than the squared correlation coefficient R2 as it makes little sense in a practical regression perspective. …”
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Hydrodynamic coefficients identification of ship simplified modular model based on support vector regression by Lifei SONG, Yuqing WANG, Wei PENG, Peiyong LI, Yushan LIu, Yongfeng ZHANG

“…ObjectivesTo address the issue of multicollinearity and parameter drift in the identification of hydrodynamic coefficients in ship separated-type models, this paper proposes a method for modeling simplified three-degree-of-freedom modular models based on support vector regression (SVR). …”
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Spatial regression analysis of land use impact on land surface temperature in four East Asian metropolises by Tzu-Ling Chen, Zih-Hong Lin, De-Cyuan Jheng

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Random Forest versus Support Vector Machine Models’ Applicability for Predicting Beam Shear Strength by Hayder Riyadh Mohammed Mohammed, Sumarni Ismail

“…Nine input combinations were constructed based on the statistical correlation to be supplied for the proposed predictive model. …”
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The Impact of Stokvel and Banking Sector Efficiency: an Econometrics Model using (ARDL) Approach to Cointegration by Ngcobo, Lindiwe

“…The negative and statistically significant coefficient of the error correction model (ECM) also confirmed the prevalence of a causal relationship between stokvel and banking sector efficiency. …”
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Particle Swarm Optimization of Support Vector Machine Inversion Model for Overhead Upright Piers Damage-Inducing Factor by Shiliang Zhou, Menghan Tang, Jun Wu, Chunru Ke

“…For intelligent monitoring of existing terminals, this research chooses Chongqing Xintian Port as the study object and proposes a support vector machine (SVM) damage-inducing factor (DIF) inversion model based on particle swarm optimization (PSO). …”
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Stochastic Models to Generate Geospatial-, Temporal-, and Cross-Correlated Daily Maximum and Minimum Temperatures by Guillermo A. Baigorria

“…The first model incorporates only spatial correlation, whereas temporal correlation using a 1-day lag and cross-correlation between variables were added to model one, respectively, by the other two models. …”
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Empirical Model of Equatorial ElectroJet (EEJ) Using Long‐Term Observations From the Indian Sector by S. Tulasi Ram, M. Ankita, B. Nilam, S. Gurubaran, Manoj Nair, Gopi K. Seemala, P. S. Brahmanandam, A. P. Dimri

“…The modeled monthly mean variations of EEJ field at ground exhibit excellent correlation of 0.96 with the observations with the root mean square error <5 nT. …”
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Research on Support Vector Regression Short-Time Traffic Flow Prediction Model for Secondary Roads Based on Associated Road Analysis by Ganglong Duan, Yutong Du, Yanying Shang, Hongquan Xue, Ruochen Zhang

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Research on Forecasting Sales of Pure Electric Vehicles in China Based on the Seasonal Autoregressive Integrated Moving Average–Gray Relational Analysis–Support Vector Regression M... by Ru Yu, Xiaoli Wang, Xiaojun Xu, Zhiwen Zhang

“…Secondly, variables that were highly correlated with sales were analyzed using gray relational analysis (GRA) and utilized as input parameters for the support vector regression (SVR) model, which was constructed to optimize sales predictions for EVs. …”
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Estimating the Compressive Strength of Cement-Based Materials with Mining Waste Using Support Vector Machine, Decision Tree, and Random Forest Models by Hongxia Ma, Jiandong Liu, Jia Zhang, Jiandong Huang

“…The beetle antennae search (BAS) algorithm was employed to tune the hyperparameters of the developed machine learning models. The predictive performances of the three models were compared by the evaluation of the values of correlation coefficient (R) and root mean square error (RMSE). …”
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Examining the Effects of Intersectoral Uncertainty Transmission Using a Time-Varying Model by Hamidreza Hamidi, Mirfeiz Fallah Shams, Hosein Jahangirnia, Mojgan Safa

“…To examine changes in cross-sectoral uncertainty contagion, the time-varying parameter vector autoregression model (TVP-VAR) is used with monthly data from January 2008 to December 2020. …”
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Height of Hydraulic Fracture Zone Based on PSO_LSSVM Model by Hebin Zhang, Tingting Wang, Bin Wu, Haijun Feng

“…At the same time, this study develops a particle swarm optimization algorithm based on adaptive inertia weight and a least squares support vector machine model to achieve height prediction of water conducting fracture zones. …”
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Machine Learning-Based Cost Estimation Models for Office Buildings by Guolong Chen, Simin Zheng, Xiaorui He, Xian Liang, Xiaohui Liao

“…It achieves stable and rapid results, with an average mean square error of 0.024, a squared correlation coefficient of 0.927, and an average percentage error of 5.52% in experiments. …”
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Groundwater fluoride modeling using an artificial neural network: a review by Neeta Kumari, Gaurav Kumar, Saahil Hembrom

“…The results of the correlation analysis help in deciding the inputs for the model. …”
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