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

“…The authors validated the TRAC algorithm on some vehicles traces. The validation indicated that the algorithm efficiency of TRAC is larger than 96%. …”
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Prediction of Middle School Students’ Recycling Behaviors with Machine Learning Algorithms by Fatma Merve Mustafaoğlu, Fatma Alkan

“…Environmentally responsible behaviors, shaped during early ages, are closely linked to environmental attitudes, as demonstrated by prior research. This study aims to predict middle school students’ recycling behaviors using machine learning algorithms. …”
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PERFORMANCE COMPARISON OF CLASSICAL ALGORITHMS AND DEEP NEURAL NETWORKS FOR TUBERCULOSIS PREDICTION by Gilgen Mate Landry, Rodolphe Nsimba Malumba, Fiston Chrisnovi Balanganayi Kabutakapua, Bopatriciat Boluma Mangata

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Algorithms for Effector Prediction in Plant Pathogens and Pests: Achievements and Current Challenges by César De los Santos-Briones, Karla Gisel Carreón-Anguiano, Sara E. Vila-Luna, Jewel Nicole Anna Todd, Ignacio Islas-Flores, Luis Sáenz-Carbonell, Pablo Alejandro Gamas-Trujillo, Blondy Canto-Canché

Subjects: “…algorithms…”
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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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Machine learning algorithms to predict the tensile strength of novel composite materials by S. Sathees Kumar, P. Shyamala, Pravat Ranjan Pati

“…Five regression algorithms such as polynomial regression, bagging regression, random forest, XGBoost, and gradient boosting were trained and evaluated using five-fold cross-validation and standard error metrics. …”
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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

“…Aiming at the phenomenon that the PageRank page sorting algorithm is prone to subject deviation, the category similarity between pages is introduced into the PageRank algorithm. …”
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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

“…The 2-days-in-advance predictions yielded (0.905 ± 0.036), recall (0.815 ± 0.057), F1 score (0.857 ± 0.035), and AP (0.905 ± 0.029). …”
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Study on the Switching Model Predictive Control Algorithm in Batch Polymerization Process by Jong Nam Kim, Chun Bae Ma, Hyok Jo, Un Chol Han, Hyon-Tae Pak, Son Il Hong, Ri Myong Kim

“…In this paper, a new switching model predictive control algorithm that can be effectively used for the temperature control of batch polymerization process is developed and its effectiveness is verified by introducing it to industrial batch polyvinyl chloride polymerization process. …”
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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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Smart Agriculture: Predicting Diseases in olive using Deep Learning Algorithms by Rahman F., Raghatate Kapesh Subhash

“…In this study, olive tree diseases are managed by improving prediction and management using a deep learning algorithm, with the aim of efficiency and accuracy of the process. …”
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Development and external validation of prediction algorithms to improve early diagnosis of cancer by J. Hippisley-Cox, CA Coupland

“…Abstract Cancer prediction algorithms are used in the UK to identify individuals at high probability of having a current, as yet undiagnosed cancer with the intention of improving early diagnosis and treatment. …”
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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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FEATURE-BASED IMPLEMENTATION OF MACHINE LEARNING ALGORITHMS FOR CARDIOVASCULAR DISEASE PREDICTION by H. Singh, R. Tripathy, P. Kumar Sarangi, U. Giri, S. Kumar Mohapatra, N. Rameshbhai Amin

“…After applying all algorithms to our data set, the experimental results concluded that the Logistic Regression model has predicted well with highest accuracy of 92% in comparison with other algorithms.…”
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