Scanning Micromirror Calibration Method Based on PSO-LSSVM Algorithm Prediction by Yan Liu, Xiang Cheng, Tingting Zhang, Yu Xu, Weijia Cai, Fengtian Han

“…The objective is to establish a correspondence between the actual deflection angle of the micromirror and the output of the measurement system employing a regression algorithm, thereby enabling the prediction of the tilt angle of the micromirror. …”
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Pose-Driven Body Shape Prediction Algorithm Based on the Conditional GAN by Jiwon Jang, Jiseong Byeon, Daewon Jung, Jihun Chang, Sekyoung Youm

“…To address these issues, we propose a lightweight algorithm that predicts body shape from clothed RGB images by leveraging pose estimation. …”
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Optimizing diabetes prediction with MLP neural networks and feature selection algorithm by Majd Mohammad A. Al-Hawamdeh

“… In this research, the goal was to improve diabetes prediction by combining Multilayer Perceptron Neural Network (MLPNN) with Memetic Algorithm (MA) and Arithmetic Optimization Algorithm (AOA). …”
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A Location Prediction Algorithm for Mobile Communications Using Directional Antennas by Xiaofeng Lu, Pietro Lio, Pan Hui, Haifei Jin

“…TRAC is composed of the location prediction and antenna adjustment. It predicts a possible circular region where the moving receiver may enter into in the near future. …”
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Extreme Gradient Boosting Algorithm for Predicting Shear Strengths of Rockfill Materials by Mahmood Ahmad, Ramez A. Al-Mansob, Kazem Reza Kashyzadeh, Suraparb Keawsawasvong, Mohanad Muayad Sabri Sabri, Irfan Jamil, Arnold C. Alguno

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Differentially Private Clustered Federated Load Prediction Based on the Louvain Algorithm by Tingzhe Pan, Jue Hou, Xin Jin, Chao Li, Xinlei Cai, Xiaodong Zhou

“…The framework can train load-forecasting models with a fast convergence rate and better prediction performance than current mainstream federated learning algorithms.…”
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Neural network and Markov based combination prediction algorithm of video popularity by Xuesen MA, Shuyou CHEN, Xiangdong XU, Zhaokun CHU

“…Caching popular video into user-side in advance improves the user experience and reduces operator costs, which is a common practice in the industry.How to effectively predict the popularity of videos has become a hot issue in the industry.On account of the shortcomings of traditional prediction algorithms such as poor nonlinear mapping ability, low prediction accuracy and weak adaptability, a video popularity prediction algorithm based on a neural network and Markov combined model (Mar-BiLSTM) was proposed.Information dependencies were preserved by constructing bidirectional memory network model (bi-directional long short-term memory, BiLSTM), the prediction accuracy of the model was further improved by using Markov properties while avoiding the increase of the complexity of the model caused by the introduction of external variables.Experimental results show that compared with traditional time series and classic neural network algorithms, the proposed algorithm improves predicting accuracy, effectiveness and reduces the amount of calculation.…”
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The Ranking Prediction of NBA Playoffs Based on Improved PageRank Algorithm by Fan Yang, Jun Zhang

“…It is of great significance to predict the results accurately based on the statistics of sports competition for participants research, commercial cooperation, advertising, and gambling profit. …”
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Actionable predictions: How designers of algorithmic systems calibrate criminal futures by Maximilian Heimstädt, Simon Egbert

“…Hopes and fears about algorithmic predictions are often rooted in the assumption that they represent a particularly actionable form of knowledge. …”
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A time series algorithm to predict surgery in neonatal necrotizing enterocolitis by Cheng Cui, Ling Qiu, Ling Li, Fei-Long Chen, Xiao Liu, Huan Sun, Xiao-Chen Liu, Lei Bao, Lu-Quan Li

“…This study develops a predictive model using the long short-term memory network (LSTM) with a focal loss (FL) to identify infants at risk of developing Bell IIB + NEC early and issue timely surgical warnings. …”
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ISLRWR: A network diffusion algorithm for drug-target interactions prediction. by Lu Sun, Zhixiang Yin, Lin Lu

“…Notably, the ISLRWR algorithm improved the area under the receiver operating characteristic curve (AUROC) by 7.53 and 5.72%, and the area under the precision-recall curve (AUPRC) by 5.95 and 4.19% compared to the RWR and MHRW algorithms, respectively, in predicting DTIs performance. …”
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Hybrid strategy enhanced crayfish optimization algorithm for breast cancer prediction by Yu-Jiong Li

Subjects: “…Crayfish optimization algorithm…”
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Sustainable Selection of Machine Learning Algorithm for Gender-Bias Attenuated Prediction by Raik Orbay, Evelina Wikner

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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

“…Once trained, these models can make predictions about future events or outcomes, such as the likelihood of a patient developing a particular disease, the risk of complications, or the effectiveness of treatment. …”
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Improved Backpropagation Using Genetic Algorithm for Prediction of Anomalies and Data Unavailability by Gunadi Widi Nurcahyo, Akbari Wafridh, Yuhandri

Subjects: “…data prediction…”
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Crime Prediction Using Decision Tree (J48) Classification Algorithm. by Ivan, Niyonzima, Emmanuel Ahishakiye, Elisha Opiyo Omulo, Danison Taremwa

Subjects: “…crime prediction; machine learning; decision tree; J48; artificial intelligence; Classification Algorithms.…”
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Numerical benchmarking of dual decomposition-based optimization algorithms for distributed model predictive control by Vassilios Yfantis, Achim Wagner, Martin Ruskowski

“…This paper presents a benchmark study of dual decomposition-based distributed optimization algorithms applied to constraint-coupled model predictive control problems. …”
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Predictive modelling of sustainable concrete compressive strength using advanced machine learning algorithms by Tejas Joshi, Pulkit Mathur, Parita Oza, Smita Agrawal

“…The results show that ML algorithms are highly effective in predicting CS, with the random forest algorithm achieving the highest accuracy (R² = 0,95; error = 3,74). …”
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Predictive modeling of electrochromic performance in ammonium metatungstate solutions using machine learning algorithms by Bocheng Jiang, Honglong Ning, Muyun Li, Rihui Yao, Chenxiao Guo, Yucheng Huang, Zijie Guo, Dongxiang Luo, Dong Yuan, Junbiao Peng

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