Machine-Learning Assisted Prediction of Spectral Power Distribution for Full-Spectrum White Light-Emitting Diode by Jiajie Fan, Yutong Li, Irena Fryc, Cheng Qian, Xuejun Fan, Guoqi Zhang

“…Then, the Back Propagation (BP) and Genetic Algorithm-Back Propagation (GA-BP) NNs are proposed to predict the spectral characteristic parameters of LEDs operated under any usage conditions. …”
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A Novel Strategy Coupling Optimised Sampling with Heterogeneous Ensemble Machine-Learning to Predict Landslide Susceptibility by Yongxing Lu, Honggen Xu, Can Wang, Guanxi Yan, Zhitao Huo, Zuwu Peng, Bo Liu, Chong Xu

Subjects: “…landslide susceptibility prediction…”
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Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…Machine learning (ML) has demonstrated potential in predicting SSIs; however, the challenge of addressing imbalanced class ratios remains. …”
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Enhancing Heart Attack Prediction: Feature Identification from Multiparametric Cardiac Data Using Explainable AI by Muhammad Waqar, Muhammad Bilal Shahnawaz, Sajid Saleem, Hassan Dawood, Usman Muhammad, Hussain Dawood

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Student dropout prediction through machine learning optimization: insights from moodle log data by Markson Rebelo Marcolino, Thiago Reis Porto, Tiago Thompsen Primo, Rafael Targino, Vinicius Ramos, Emanuel Marques Queiroga, Roberto Munoz, Cristian Cechinel

“…In particular, we employed the CatBoost algorithm, trained on student activity logs from the Moodle platform. …”
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Predicting student performance academic using Automated Machine Learning (AutoML): in medical academic institutions by Rania A. Abougalala, Nouf Alharbi, Mohamed A. Amasha, Marwa F. Areed, Salem Alkhalaf, Dalia Khairy

“…Abstract Educational institutions seek to increase distinguished educational programs, and these programs increase costs and expenses of these institutions consuming a lot of their budget. …”
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Siamese Graph Convolutional Split-Attention Network with NLP based Social Sentimental Data for enhanced stock price predictions by Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni

“…Finally, a Graph Convolutional Split-Attention Network (SGCSAN) for promisingly predicting whether the stock prices are going to hit the ground and fly high again or is going to nosedive with Humboldt Squid Optimization Algorithm (HSOA) is introduced to further improve accuracy with lesser error generation. …”
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Constant time lattice reduction in dimension 4 with application to SQIsign by Otto Hanyecz, Alexander Karenin, Elena Kirshanova, Péter Kutas, Sina Schaeffler

“… In this paper we propose a constant time lattice reduction algorithm for integral dimension-4 lattices. …”
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Ensemble-Based Neighborhood Attribute Reduction: A Multigranularity View by Yuan Gao, Xiangjian Chen, Xibei Yang, Pingxin Wang, Jusheng Mi

“…Different from traditional process which computes reduct through employing a fixed granularity, our algorithm aims to obtain reduct from the viewpoint of multigranularity. …”
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Domain general noise reduction for time series signals with Noisereduce by Tim Sainburg, Asaf Zorea

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Rough decision rules extraction and reduction based on granular computing by Hong-can YAN, Feng ZHANG, Bao-xiang LIU

“…Rule mining was an important research content of data mining,and it was also a hot research topic in the fields of decision support system,artificial intelligence,recommendation system,etc,where attribute reduction and minimal rule set extraction were the key links.Most importantly,the efficiency of extraction was determined by its application.The rough set model and granular computing theory were applied to the decision rule reduction.The decision table was granulated by granulation function,the grain of membership and the concept granular set construction algorithm gener-ated the initial concept granular set.Therefore,attribute reduction could be realized by the distinguish operator of concept granule,and decision rules extraction could be achieved by visualization of concept granule lattice.Experimental result shows that the method is easier to be applied to computer programming and it is more efficient and practical than the existing methods.…”
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Residual-conditioned sparse transformer for photoacoustic image artifact reduction by Xiaoxue Wang, Jinzhuang Xu, Chenglong Zhang, Moritz Wildgruber, Wenjing Jiang, Lili Wang, Xiaopeng Ma

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Model-Order Reduction of Multistage Cascaded Models for Digital Predistortion by Raul Criado, Wantao Li, William Thompson, Gabriel Montoro, Kevin Chuang, Pere L. Gilabert

“…To reduce the computational complexity of these multistage CC behavioral models, a model-order reduction technique based on a greedy algorithm is proposed. …”
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TEMPTED: time-informed dimensionality reduction for longitudinal microbiome studies by Pixu Shi, Cameron Martino, Rungang Han, Stefan Janssen, Gregory Buck, Myrna Serrano, Kouros Owzar, Rob Knight, Liat Shenhav, Anru R. Zhang

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Edge Server Placement and Task Allocation for Maximum Delay Reduction by Koki Shibata, Sumiko Miyata

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Multi-Condition Magnetic Core Loss Prediction and Magnetic Component Performance Optimization Based on Improved Deep Forest by Haotian Shi, Zipeng Jin

“…This paper proposes a core loss prediction model based on an improved deep forest algorithm and information entropy-enhanced genetic algorithm. …”
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Accurate Prediction of 327 Rice Variety Growth Period Based on Unmanned Aerial Vehicle Multispectral Remote Sensing by Zixuan Qiu, Hao Liu, Lu Wang, Shuaibo Shao, Can Chen, Zijia Liu, Song Liang, Cai Wang, Bing Cao

“…In this study, multispectral images of rice at various growth stages were captured using an unmanned aerial vehicle, and single-plant rice silhouettes were identified for 327 rice varieties by establishing a deep-learning algorithm. A growth stage prediction method was established for the 327 rice varieties based on the normalized vegetation index combined with cubic polynomial regression equations to simulate their growth changes, and it was first proposed that the growth stages of different rice varieties were inferred by analyzing the normalized difference vegetation index growth rate. …”
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Research on prediction of bottom hole flowing pressure for vertical coalbed methane wells based on improved SSA-BPNN by YU Yang, DONG Yintao, LI Yunbo, BAO Yu, ZHANG Lixia, SUN Hao

Subjects: “…|coalbed methane|sparrow search algorithm|neural network|bottom hole flowing pressure|prediction model…”
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An Adaptive Maximum Power Output Sustaining System for a Photovoltaic Power Plant Based on a Robust Predictive Control Approach by I. Elzein, Yu. N. Petrenko

“…This paper makes an emphasis on model predictive controller as a control method for controlling the maximum power point tracking through the utilization of the well-known algorithm namely the Perturb and Observe technique. …”
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Improving of the Generation Accuracy Forecasting of Photovoltaic Plants Based on <i>k</i>-Means and <i>k</i>-Nearest Neighbors Algorithms by P. V. Matrenin, A. I. Khalyasmaa, V. V. Gamaley, S. A. Eroshenko, N. A. Papkova, D. A. Sekatski, Y. V. Potachits

“…For this, it is also proposed to use studied the feature space dimensionality reduction algorithm to visualize and estimate the clustering accuracy. …”
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