Improved Variational Bayes for Space-Time Adaptive Processing by Kun Li, Jinyang Luo, Peng Li, Guisheng Liao, Zhixiang Huang, Lixia Yang

“…Furthermore, this method fully exploits the joint sparsity of the Multiple Measurement Vector (MMV) model to achieve greater sparsity without compromising accuracy, and employs a first-order Taylor expansion to eliminate grid mismatch in the dictionary. …”
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Improve the Accuracy of Support Vector Machine Using Chi Square Statistic and Term Frequency Inverse Document Frequency on Movie Review Sentiment Analysis by Ukhti Ikhsani Larasati, Much Aziz Muslim, Riza Arifudin, Alamsyah Alamsyah

“…Data processing can be done with text mining techniques. …”
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PRINCIPAL COMPONENT ANALYSIS-VECTOR AUTOREGRESSIVE INTEGRATED (PCA-VARI) MODEL USING DATA MINING APPROACH TO CLIMATE DATA IN THE WEST JAVA REGION by Devi Munandar, Budi Nurani Ruchjana, Atje Setiawan Abdullah

“…Pre-processing is an analysis of raw climate data. The data mining process determines the proportion of each component of PCA and is selected as variables in the VARI process. …”
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Comparison of Support Vector Machine (SVM) and Random Forest (RF) Algorithm Performance with Random Undersampling Technique to Predict Gestational Diabetes Mellitus Risk by Annisa Damayanti, Anna Baita

“…Gestational Diabetes Mellitus (GDM) is a condition of glucose intolerance that develops during pregnancy until the birth process, which is characterized by an abnormal increase in blood sugar levels. …”
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A Method to Detect Concealed Damage in Concrete Tunnels Using a Radar Feature Vector and Bayesian Analysis of Ground-Penetrating Radar Data by Junfang Wang, Heng Chen, Jianfu Lin, Xiangxiong Li

“…This study presents a probabilistic, data-driven method for GPR-based damage detection, which exempts the requirement in the training process of supervised ML models. The approach involves extracting a radar feature vector (RFV), building a Bayesian baseline model with healthy data, and quantifying damage severity with the Bayes factor. …”
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Klasifikasi Ulasan Palsu Menggunakan Borderline Over Sampling (BOS) dan Support Vector Machine (SVM) (Studi Kasus : Ulasan Tempat Makan) by Aisyah Awalina, Fitra Abdurrachman Bachtiar, Indriati Indriati

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Prediction of the Strength Properties of Carbon Fiber-Reinforced Lightweight Concrete Exposed to the High Temperature Using Artificial Neural Network and Support Vector Machine by Harun Tanyildizi

“…The artificial neural network and support vector machine were used to estimate the compressive strength and flexural strength of carbon fiber-reinforced lightweight concrete with the silica fume exposed to the high temperature. …”
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Prediction of Pile Bearing Capacity Using Opposition-Based Differential Flower Pollination-Optimized Least Squares Support Vector Regression (ODFP-LSSVR) by Nhat-Duc Hoang, Xuan-Linh Tran, Thanh-Canh Huynh

“…Least squares support vector regression (LSSVR) is used for analyzing a dataset containing historical records of pile tests. …”
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An Investigation of the Impact of Health Expenditures on International Migration as a Pull Factor in OECD Countries Using a Panel Vector Autoregression (PVAR) Approach by Serdar Öztürk, Buket Altınöz

“…In addition to being a demographic phenomenon, it is also a complex process that develops depending on the decision-making mechanisms of individuals. …”
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Boruta-grid-search least square support vector machine for NO2 pollution prediction using big data analytics and IoT emission sensors by Habeeb Balogun, Hafiz Alaka, Christian Nnaemeka Egwim

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MODEL OF A MATRIX CROSSCORRELATION FUNCTION OF THE PROBING AND REFLECTED VECTOR SIGNALS FOR A CONCEPTUAL DESIGN OF A SYNTHETIC APERTURE RADAR ON AN AERIAL CARRIER by R. N. Akinshin, O. V. Esikov, D. A. Zatuchny, A. V. Peteshov

“…Taking into account the developed models for the formation of the vector sounding signal and the matrix response function of the distributed radar object, a block-diagram of the model of the matrix cross-correlation function of the emitted and reflected vector signals is proposed. …”
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The Influence of Contexts in the Process of Choosing a University Product by Dumitru Miron, Raluca Ecaterina Brandabur, Daniel Nicolae Măiță, Flavius Cosmin Darie, Dumitru Goldbach, Ion-Dănuț Lixandru

“…Furthermore, the research sought to establish the desirable level of econometric robustness of the basic vectors in the decision-making process regarding the selection of a specific set of competencies and cognitive skills promised by the study programmes. …”
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Support Vector Machine for Prediction of the Electronic Factors of a Schottky Configuration Interlaid with Pure PVC and Doped by Sm2O3 Nanoparticles by Yashar Azizian‐Kalandaragh, Ali Barkhordari, Yosef Badali

“…By contrasting the predicted and experimental results, the predictive ability of the SVM approach for predicting the electronic specifications of the fabricated structures and their current conduction/transport processes has been evaluated to investigate the effectiveness of the SVM. …”
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Damage Classification Approach for Concrete Structure Using Support Vector Machine Learning of Decomposed Electromechanical Admittance Signature via Discrete Wavelet Transform by Jingwen Yang, Demi Ai, Duluan Zhang

“…Then these indicators, incorporated with traditional ones including root mean square deviation (RMSD), baseline-changeable RMSD named RMSDk, correlation coefficient (CC), and mean absolute percentage deviation (MAPD), were processed by a support vector machine (SVM) model, and finally damage type could be automatically classified and identified. …”
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Synergizing remote sensing, support vector machine, and aeromagnetic data for precise lithological and mineral potential mapping: a case study from Egypt by Hatem M. El-Desoky, Ahmed M. Abdel-Rahman, Hamada El-Awny, Wael Fahmy, Reda Abdu Yousef El-Qassas, Kamal Abdelrahman, Hassan Alzahrani, Peter Andráš, Yahia Z. Amer, Ahmed M. Eldosouky

“…Therefore, we effectively mapped the exposed rock units in the Hamash region of the Eastern Desert of Egypt by using Support Vector Machine (SVM) to Sentinel 2 data through executing machine learning algorithms (MLAs). …”
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A New Two-Dimensional Electromagnetic Field Analysis and Loss Calculation Method for High-Frequency Applications Based on Vector Magnetic Circuit Theory by Chengbo Li, Ming Cheng, Wei Wang

“…The loss calculation of commercial finite element software is usually in the post-processing phase, making the loss calculation and electromagnetic field analysis irrelevant. …”
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Optimization of multi-element geochemical anomaly recognition in the Takht-e Soleyman area of northwestern Iran using swarm-intelligence support vector machine by Hamid Sabbaghi, Seyed Hassan Tabatabaei, Nader Fathianpour

“…The grasshopper-optimized support vector machine was proven to be a rigorous approach for detecting multi-element geochemical anomalies and can also be extended to other geoscientific applications. …”
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Cross-correlation-based signal pruning method (CCSPM) for effective signal distortion reduction in massive MIMO communications by M. Kasiselvanathan, SatheeshKumar Palanisamy, N. Sathishkumar, K. B. Gurumoorthy, Tagrid Abdullah N. Alshalali, S. Lakshmi Narayanan

“…The process is validated using linear vector learning through which the signal vector representations are pursued. …”
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PM2.5 Concentration Prediction Based on Markov Blanke Feature Selection and Hybrid Kernel Support Vector Regression Optimized by Particle Swarm Optimization by Lian-Hua Zhang, Ze-Hong Deng, Wen-Bo Wang

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A wireless sensor data-based coal mine gas monitoring algorithm with least squares support vector machines optimized by swarm intelligence techniques by Peng Chen, Yonghong Xie, Pei Jin, Dezheng Zhang

“…In order to assess the risks arisen from gas explosion or gas poisoning, wireless sensor data should be processed and classified efficiently. Due to the fact that the “negative samples” of coal mine safety data are scarce, least squares support vector machine is introduced to deal with this problem. …”
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