Machine learning opportunities to predict obstetric haemorrhages by Yu. S. Boldina, A. A. Ivshin

“…Machine learning is based on computer algorithms, the most common among them in medicine are the decision tree (DT), naive Bayes classifier (NBC), random forest (RF), support vector machine (SVM), artificial neural network (ANNs), deep neural network (DNN) or deep learning (DL) and convolutional neural network (CNN). …”
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Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning by Lucijano Berus, Jernej Hernavs, David Potocnik, Kristijan Sket, Mirko Ficko

“…Different machine learning algorithms, such as Random Forest (RF), k-nearest neighbors (k-NN), and Decision Trees (DT), were used for predictive modeling. …”
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Machine Learning in the National Economy by Azamjon A. Usmonov

“…Through the use of advanced algorithms and tools, such as linear regression, decision trees, and neural networks, it is possible to effectively model and predict key macroeconomic indexes, including GDP growth, inflation, and financial risks. …”
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Wearable IoT (w-IoT) artificial intelligence (AI) solution for sustainable smart-healthcare by Gurdeep Singh

“…It covers performance results rendering research science communication on machine learning models for time series analysis, regression and classification to implement defined and adaptive thresholds, adopting standard deviation and moving average, computing mean square error (MSE), root mean square error (RSME) and mean absolute error (MAE) values, utilizing exponential moving average results on multiple features, prominently targeting resting heartrate data. Machine Learning algorithms for classification with higher F-score or performance metrics adopted are Decision Trees (DT), K-Nearest Neighbours (KNN), XGboost, One-class SVM and Logistic Regression. …”
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Advancements in Machine Learning-Based Intrusion Detection in IoT: Research Trends and Challenges by Márton Bendegúz Bankó, Szymon Dyszewski, Michaela Králová, Márton Bertalan Limpek, Maria Papaioannou, Gaurav Choudhary, Nicola Dragoni

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Climate change reduces and shifts suitable habitats of Uapaca kirkiana Müll. Arg. to higher altitudes in Malawi by Bruno Kokouvi Kokou, Msiska Ulemu, Wouyo Atakpama, Séverin Biaou, Soloum Clément Teteli, Kouagou Raoul Sambieni, Frank Mnthambala, Tembo Mavuto, Paul Munyenyembe, Florent Noulèkoun

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Assessing wildfire susceptibility in Iran: Leveraging machine learning for geospatial analysis of climatic and anthropogenic factors by Ehsan Masoudian, Ali Mirzaei, Hossein Bagheri

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PENERAPAN PARTICLE SWARM OPTIMIZATION PADA ALGORITMA C 4.5 UNTUK SELEKSI PENERIMAAN KARYAWAN by Agus Wiyatno

“…Model algorithms are widely used in research related to the employee is C4.5 decision tree classification model. …”
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EBOC: Ensemble-Based Ordinal Classification in Transportation by Pelin Yıldırım, Ulaş K. Birant, Derya Birant

“…This article also compares the proposed EBOC approach with ordinal class classifier and traditional tree-based classification algorithms (i.e., C4.5 decision tree, RandomTree, and REPTree) in terms of accuracy. …”
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Longest Path Reroute to Optimize the Optical Multicast Routing in Sparse Splitting WDM Networks by Huanlin Liu, Hongyue Dai, Fei Zhai, Yong Chen, Chengying Wei

“…Simulation results show that the proposed algorithm can get the low-cost multicast tree and reduce the required number of wavelength channels.…”
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Reductions of GKZ systems and applications to cosmological correlators by Thomas W. Grimm, Arno Hoefnagels

“…We motivate the need for such reduction techniques by considering cosmological correlators on an FRW space-time and solve the tree-level single-exchange correlator in this way. …”
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Development of clinical decision support for patients older than 65 years with fall-related TBI using artificial intelligence modeling. by Biche Osong, Eric Sribnick, Jonathan Groner, Rachel Stanley, Lauren Schulz, Bo Lu, Lawrence Cook, Henry Xiang

“…Data were split into two sets, where 80% developed a decision tree, and 20% tested predictive performance. We employed a conditional inference tree algorithm with bootstrap (B = 100) and grid search options to grow the decision tree and measure discrimination ability using the area under the curve (AUC) and calibration plots.…”
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A Performance Analysis of Business Intelligence Techniques on Crime Prediction by Ivan, Niyonzima, Emmanuel Ahishakiye, Elisha Opiyo Omulo, Ruth Wario

“…Four different classification algorithms that is; decision tree (J48), Naïve Bayes, Multilayer Perceptron and Support Vector Machine were compared to find the most effective algorithm for crime prediction. …”
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GEOGRAPHICALLY WEIGHTED MACHINE LEARNING MODEL FOR ADDRESSING SPATIAL HETEROGENEITY OF PUBLIC HEALTH DEVELOPMENT INDEX IN JAVA ISLAND by Muhammad Azis Suprayogi, Bagus Sartono, Khairil Anwar Notodiputro

“…Random Forest (RF) machine learning models have emerged as a prominent algorithm, addressing problems arising from the sole use of decision trees, such as overfitting and instability. …”
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Detecting Fraudulent Transaction in Banking Sector Using Rule-Based Model and Machine Learning by Cut Dinda Rizki Amirillah

“…This research aims to develop an effective fraud detection model in banking transactions using the rule-based model (RBM) approach and the isolation forest (IF) machine learning algorithm. Based on data from the Ministry of Communication and Information Technology, there were more than 405,000 online fraud cases during the 2019–2022 period, indicating the need for a reliable fraud detection system to protect customers. …”
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Adaptive Resource Optimization for IoT-Enabled Disaster-Resilient Non-Terrestrial Networks using Deep Reinforcement Learning by Fathe Jeribi, R. John Martin

“…Initially, we design the chaotic plum tree (CPT) algorithm for clustering IoT nodes to maximize the number of satisfactory connections, ensuring all nodes meet sustainability requirements in terms of delay and QoS. …”
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Real-time path planning for Mecanum-wheeled robots with type-2 fuzzy logic controller by Thanh-Lam Bui, Duc-Quang Nguyen, Van-Truong Nguyen

“…In addition, in many applications, robots need to operate automatically and find the optimal path. …”
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Analysis of Encrypted Network Traffic for Enhancing Cyber-security in Dynamic Environments by Faeiz Alserhani

“…As a result, there is a fundamental need for methodologies based on intelligent analysis of patterns and attributes of encrypted network traffic. …”
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An Approach to Truck Driving Risk Identification: A Machine Learning Method Based on Optuna Optimization by Zhaofei Wang, Hao Li, Qiuping Wang

“…Combining the running time, precision, recall, and F1-Score, the LightGBM model optimized based on the Tree-structured Parzen Estimator (TPE) algorithm has the best performance with a precision of 0.98. …”
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Machine learning techniques for predicting the peak response of reinforced concrete beam subjected to impact loading by Ali Husnain, Munir Iqbal, Hafiz Ahmed Waqas, Mohammed El-Meligy, Muhammad Faisal Javed, Rizwan Ullah

“…To address these challenges, this study investigates various ensemble and non-ensemble machine learning techniques—including support vector machine, gaussian process regression (GPR), k-nearest neighbor (KNN), gene expression programming, random forest, decision tree, boosted tree, adaptive boosting tree, gradient boosting algorithm, stochastic gradient descent, and artificial neural network—for predicting the peak response of RC beams under impact loads. …”
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