PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

“…The name "machine learning" refers to the automated detection of meaningful patterns in large data sets.  …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

“…The name "machine learning" refers to the automated detection of meaningful patterns in large data sets.  …”
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Advanced Methodology for Fraud Detection in Energy Using Machine Learning Algorithms by Silviu Gresoi, Grigore Stamatescu, Ioana Făgărășan

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Predicting agricultural drought in central Europe by using machine learning algorithms by Endre Harsányi

“…Thus, this research evaluates the patterns and magnitude of agriculture droughts using Standardized Precipitation Evapotranspiration Index (SPEI) from 1926 to 2020 in eastern Hungary, and assess the performance of six machine learning models (Random Forest (RF), Extra Trees (ET), Gradient Boosting (GB), Extreme Gradient Boost (XGB), Support Vector Machines (SVM), and Multi-Layer Perceptron (ANN-MLP)) in predicting agriculture droughts. …”
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Purchasing Prediction Using Machine Learning Algorithms for Optimizing Inventory Management by Reza Hamdi Prayetno, Rani Destika Purba, Kyrene Wirawan, Kelvin Sweet, Evta Indra

“…Along with technological developments, traditional methods of inventory management are starting to be replaced by data-based approaches and machine learning algorithms. The use of machine learning is not only limited to predicting purchasing needs, but can also be applied in various other business aspects. …”
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Application of machine learning algorithm to predict the behavior of stocks marketed in Brazil by Gabriel Donadio Costa, Rogério João Lunkes

“…This work analyzes the application of machine learning algorithms in the selection of portfolios in the Brazilian market. …”
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Healthcare Prediction Using Novel Machine Learning Methods and Metaheuristic Algorithm by Yazdan Ashgevari, Behrouz Alefy, Faranak Kazemi

“…ML models are trained on historical healthcare data to learn patterns and relationships between different variables. …”
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Live Weight Prediction in Norduz Sheep Using Machine Learning Algorithms by Cihan Çakmakçı

“…There were no differences between the means of actual and predicted LWs by machine learning models. The fact that the models generalized well on the testing data sets indicates that machine learning algorithms have valid predictive patterns and are effective methods in LW weight of Norduz sheep. …”
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Diverse regulated cell death patterns and immune traits in kidney allograft with fibrosis: a prediction of renal allograft failure based on machine learning, single-nucleus RNA seq... by Yuqing Li, Jiandong Zhang, Xuemeng Qiu, Yifei Zhang, Jiyue Wu, Qing Bi, Zejia Sun, Wei Wang

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A Cloud-Based Intelligence System for Asian Rust Risk Analysis in Soybean Crops by Ricardo Alexandre Neves, Paulo Estevão Cruvinel

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Evaluation of machine learning algorithms in tunnel boring machine applications: a case study in Mashhad metro line 3 by Morteza Abbasi, Amir Hossein Namadchi, Mehdi Abbasi, Mohsen Abbasi

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A Novel Improved Local Binary Pattern and Its Application to the Fault Diagnosis of Diesel Engine by Yanping Cai, Guanghua Xu, Aihua Li, Xu Wang

“…To effectively make use of the component spatial information in time-frequency images, local binary pattern (LBP) algorithm is applied. Also, in view of the problems that traditional LBP coding is easily interfered by singular pixel points and the relative spatial information is not prominent, an improved coding rule of the LBP operator is put forward in this paper. …”
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Stock Index Prices Prediction via Temporal Pattern Attention and Long-Short-Term Memory by Xiaolu Wei, Binbin Lei, Hongbing Ouyang, Qiufeng Wu

“…The study’s motivation is based on the notion that datasets of stock index prices involve weak periodic patterns, long-term and short-term information, for which traditional approaches and current neural networks such as Autoregressive models and Support Vector Machine (SVM) may fail. …”
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Identification of hub genes for the diagnosis associated with heart failure using multiple cell death patterns by Hua‐jing Yuan, Hui Yu, Yi‐ding Yu, Xiu‐juan Liu, Wen‐wen Liu, Yi‐tao Xue, Yan Li

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Detection and Pattern Recognition of Chemical Warfare Agents by MOS-Based MEMS Gas Sensor Array by Mengxue Xu, Xiaochun Hu, Hongpeng Zhang, Ting Miao, Lan Ma, Jing Liang, Yuefeng Zhu, Haiyan Zhu, Zhenxing Cheng, Xuhui Sun

“…Finally, principal component analysis (PCA) and machine learning algorithms were applied for CWA classification. …”
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Exoskeleton-guided passive movement elicits standardized EEG patterns for generalizable BCIs in stroke rehabilitation by Xinyi Zhang, Lanfang Xie, Wanting Liu, Shaoying Liang, Liyao Huang, Mingjun Wang, Lingling Tian, Li Zhang, Zhen Liang, Hai Li, Gan Huang

“…Time and time-frequency domain analyses were performed to examine the event-related potential (ERP), event-related desynchronization (ERD), and synchronization (ERS) patterns. The performance of two BCI algorithms, Common Spatial Patterns (CSP) and EEGNet, was evaluated in both within-subject and cross-subject decoding tasks. …”
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Machine learning algorithms to detect patient–ventilator asynchrony: a feasibility study by Guillermo Gutierrez, Kendrew Wong, Arun Jose, Jeffrey Williams

“…We explored the feasibility of using machine learning algorithms to replicate the assessment of breathing patterns by experienced clinicians, based on airway flow and pressure signals. …”
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Image Reconstruction Algorithm Based on Extreme Learning Machine for Electrical Capacitance Tomography by SU Ziheng, CHEN Deyun, WANG Lili

“…Aiming at the problem that the traditional ECT is not accurate in complex situations, this paper proposes a depth learning based inversion method Through the improvement and optimization of the traditional extreme learning machine, the image feature information obtained by the reconstructed image method is used as the training data, and the result obtained by inputting the data into the predictive model is used as the prior information The cost function is used to encapsulate the prior knowledge and domain expertise, and spatial regularizers and time regularizers are introduced to enhance sparsity The separated Bregman (SB) algorithm and the iterative shrinkage threshold (FIST) method are used to solve the specified cost function The final imaging result is obtained The simulation results show that the image reconstructed by this method has less than 10% error compared with the original flow pattern, and reduces artifacts and distortion, which improves the reconstructed image quality…”
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Botnet Detection Using Support Vector Machines with Artificial Fish Swarm Algorithm by Kuan-Cheng Lin, Sih-Yang Chen, Jason C. Hung

“…The proposed method is a classified model in which an artificial fish swarm algorithm and a support vector machine are combined. …”
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Estimation Algorithm of Machine Operational Intention by Bayes Filtering with Self-Organizing Map by Satoshi Suzuki, Fumio Harashima

“…We present an intention estimator algorithm that can deal with dynamic change of the environment in a man-machine system and will be able to be utilized for an autarkical human-assisting system. …”
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