Distribution Network Reconfiguration for Power Loss Reduction and Voltage Profile Improvement Using Chaotic Stochastic Fractal Search Algorithm by Tung Tran The, Dieu Vo Ngoc, Nguyen Tran Anh

“…This paper proposes a chaotic stochastic fractal search algorithm (CSFSA) method to solve the reconfiguration problem for minimizing the power loss and improving the voltage profile in distribution systems. …”
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Feature dimensionality reduction for recognition of Persian handwritten letters using a combination of quantum genetic algorithm and neural network by Mohammad Javad Aranian, Moein Sarvaghad-Moghaddam, Monireh Houshmand

Subjects: “…Dimensionality reduction of features…”
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Shape-Matching: A Novel Algorithm To Define The Optimal Reduction Endpoint In Operative Management Of Proximal Humeral Fractures (PHF) by Simon Martin Lambert, Peter Varga, Martin Jaeger, Karen Mys, Luke Visscher, Sara Lindenmann, Torsten Pastor, Paolo Antonacci, Matthias Knobe

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A Low-Complexity Block Diagonalization Algorithm for MU-MIMO Two-Way Relay Systems with Complex Lattice Reduction by Lin Xiao, Shengen Liu, Dingcheng Yang

“…To reduce the complexity of proposed precoding scheme, we employ the QR decomposition and complex lattice reduction (CLR) transform to replace the two times singular value decomposition (SVD) of conventional BD-based precoding algorithm by introducing a combined channel inversion to eliminate the multiple users interference (MUI). …”
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Multi-Degree Reduction of Said–Ball Curves and Engineering Design Using Multi-Strategy Enhanced Coati Optimization Algorithm by Feng Zou, Xia Wang, Weilin Zhang, Qingshui Shi, Huogen Yang

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Multi-Dimensional Feature Fusion and Enhanced Attention Streaming Movie Prediction Algorithm by Hanqing Hu, Tianmu Tian, Chengjing Liu, Xueyuan Bai

“…The experimental results show that the proposed algorithm FFLSTMEA achieves better prediction results with an average absolute error (MAE) of 3.50, a root mean square error (RMSE) of 5.28, and a coefficient of determination (R-squared) of 0.87 in the evaluation index. …”
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Energy-Efficient Prediction Clustering Algorithm for Multilevel Heterogeneous Wireless Sensor Networks by Jian Peng, Tang Liu, Hongyou Li, Bing Guo

“…This paper presents research on the existing clustering algorithm applied in heterogeneous sensor networks and then puts forward an energy-efficient prediction clustering algorithm, which is adaptive to sensor networks with energy and objects heterogeneous. …”
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Machine learning algorithm to predict in-hospital mortality after aneurysmal subarachnoid hemorrhage by Juri V. Kivelev, Alexey L. Krivoshapkin, Albert A. Sufianov

“…The best model for predicting lethal outcome was LSTM. After comparison with other ML algorithms LSTM showed the highest predictive values (AUROC – 0.83; 95% CI: 0.72–0.92, AURPC – 0.62; 95% CI 0.39–0.81) in term of in-hospital mortality. …”
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Prediction of pulmonary embolism by an explainable machine learning approach in the real world by Qiao Zhou, Ruichen Huang, Xingyu Xiong, Zongan Liang, Wei Zhang

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Prediction and diagnosis of cardiovascular disease using cloud and machine learning design by K. Babu, A. Gokula Chandar, S. Kannadhasan

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Predictive channel scheduling algorithm between macro base station and micro base station group by Yinghai XIE, Ruohe YAO, Bin WU

“…A novel predictive channel scheduling algorithm was proposed for non-real-time traffic transmission between macro-base stations and micro-base stations in 5G ultra-cellular networks.First,based on the stochastic stationary process characteristics of wireless channels between stationary communication agents,a discrete channel state probability space was established for the scheduling process from the perspective of classical probability theory,and the event domain was segmented.Then,the efficient scheduling of multi-user,multi-non-real-time services was realized by probability numerical calculation of each event domain.The theoretical analysis and simulation results show that the algorithm has low computational complexity.Compared with other classical scheduling algorithms,the new algorithm can optimize traffic transmission in a longer time dimension,approximate the maximum signal-to-noise ratio algorithm in throughput performance,and increase system throughput by about 14% under heavy load.At the same time,the new algorithm is accurate.Quantitative computation achieves a self-adaption match between the expected traffic rate and the actual scheduling rate.…”
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Predictive machine learning algorithm for COPD exacerbations using a digital inhaler with integrated sensors by Michael Reich, Njira Lugogo, Laurie D Snyder, Megan L Neely, Guilherme Safioti, Randall Brown, Michael DePietro, Roy Pleasants, Thomas Li, Lena Granovsky

“…This analysis aimed to determine if a machine learning algorithm capable of predicting impending exacerbations could be developed using data from an integrated digital inhaler.Patients and methods A 12-week, open-label clinical study enrolled patients (≥40 years old) with COPD to use ProAir Digihaler, a digital dry powder inhaler with integrated sensors, to deliver their reliever medication (albuterol, 90 µg/dose; 1–2 inhalations every 4 hours, as needed). …”
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Safety-critical nonlinear optimal predictive control with adaptive error elimination algorithm for robotic system by Wang Helin

Subjects: “…nonlinear optimal predictive control…”
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Advanced predictive disease modeling in biomedical IoT using the temporal adaptive neural evolutionary algorithm by Chandragandhi S, Arvind C, Srihari K

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Predictive modeling of adolescent suicidal behavior using machine learning: Key features and algorithmic insights by Priya Metri, Swetta Kukreja

“…Among these, Random Forest and SVM emerged as the most commonly used algorithms, featured in 35 % and 27 % of studies respectively. …”
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Application of Artificial Intelligence for the Implementation of Mismatch Negativity Potential Algorithms in Industrial Automated Predictive Maintenance Systems by Alexander Yu. Chesalov

“…To study the possibility of using artificial intelligence technologies to implement algorithms based on the potential of mismatch negativity (MMN) and the possibility of their application in industrial automated systems of predictive or prescriptive maintenance, as well as to develop a basic MMN algorithm and implement it in the Python programming language.Results. …”
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Application of smart technologies for predicting soil erosion patterns by Rana Muhammad Adnan Ikram, Mo Wang, Hossein Moayedi, Atefeh Ahmadi Dehrashid, Shiva Gharibi, Jing-Cheng Han

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Construction and validation of a predictive model for suicidal ideation in non-psychiatric elderly inpatients by Shuyun Xiong, Dongxu Si, Meizhu Ding, Cuiying Tang, Jinling Zhu, Danni Li, Ying Lei, Lexian Huang, Xiaohua Chen, Jicai Chen

Subjects: “…Machine learning algorithms…”
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Predictive algorithms and criminal justice: expectations, challenges and a particular view of the Spanish VioGén system by Pilar Martín Ríos

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Comparative Study of Random Forest and Gradient Boosting Algorithms to Predict Airfoil Self-Noise by Shantaram B. Nadkarni, G. S. Vijay, Raghavendra C. Kamath

“…Hence, there is a need to predict airfoil noise. This paper uses the airfoil dataset published by NASA (NACA 0012 airfoils) to predict the scaled sound pressure using five different input features. …”
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