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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Decision Tree Methodology (C4.5) for Predicting Students' Reading Interest in the Library SMK Negeri 1 Kota Cirebon by Muhammad Erwanto, Kosim Kosim, Nur Bambang Riyanto, Sukmo Banyu Jogo

“…This study uses data mining techniques with the C4.5 algorithm to predict student reading interest. This research produces rules to help SMK N 1 Cirebon City predict student reading interest in the school library. …”
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Application of log-based specific surface area prediction for permeability modeling in a highly heterogeneous carbonate reservoir in the middle east by Mojtaba Homaie, Ida Lykke Fabricius, Morten Leth Hjuler, Asadollah Mahboubi, Ali Kadkhodaie, Reza Moussavi Harami

“…This study evaluates two log-based methodologies for specific surface modeling and their role in predicting permeability. The first method utilizes density and gamma-ray logs, as previously validated in North Sea chalks, while the second method innovatively integrates deep resistivity and porosity data using a K-nearest neighbor machine learning algorithm. …”
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Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques by Tuğçe Öznacar, Nuray Varol Kayapunar

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Cutting-edge approaches to specific energy prediction in TBM disc cutters: Integrating COSSA-RF model with three interpretative techniques by Jian Zhou, Zijian Liu, Chuanqi Li, Kun Du, Haiqing Yang

“…Therefore, in this paper, the sparrow search algorithm (SSA), combined with six chaotic mapping strategies, is utilized to optimize the random forest (RF) model for predicting SE, referred to as the COSSA-RF prediction models. …”
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Comparison of Univariate and Multivariate Applications of GBLUP and Artificial Neural Network for Genomic Prediction of Growth and Carcass Traits in the Brangus Heifer Population by Sunday O. Peters, Kadir Kızılkaya, Mahmut Sinecen, Milt G. Thomas

Subjects: “…genomic prediction…”
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Improved Pacific Decadal Oscillation Prediction by an Optimizing Model Combined Bidirectional Long Short-Term Memory and Multiple Modal Decomposition by Hang Yu, Junbo Lei, Pengfei Lin, Tao Zhang, Hailong Liu, Huilin Lai, Lindong Lai, Bowen Zhao, Bo Wu

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Development of a Self-Updating System for the Prediction of Steel Mechanical Properties in a Steel Company by Machine Learning Procedures by Valerio Zippo, Elisa Robotti, Daniele Maestri, Pietro Fossati, David Valenza, Stefano Maggi, Gennaro Papallo, Masho Hilawie Belay, Simone Cerruti, Giorgio Porcu, Emilio Marengo

“…The proposed approach has a comprehensive connotation, starting from data pre-treatment and cleaning, to model building and prediction. Different machine learning algorithms are compared (Polynomial Regression, LASSO, Random Forests and Gradient Boosting, ANN, SVM, and k-NN), to provide the best predictive ability, also exploiting human reinforcement. …”
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Leveraging explainable artificial intelligence with ensemble of deep learning model for dementia prediction to enhance clinical decision support systems by Mohamed Medani, Ghada Moh. Samir Elhessewi, Mohammed Alqahtani, Somia A. Asklany, Sulaiman Alamro, Da’ad Albalawneh, Menwa Alshammeri, Mohammed Assiri

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A Novel Approach Utilizing Bagging, Histogram Gradient Boosting, and Advanced Feature Selection for Predicting the Onset of Cardiovascular Diseases by Norma Latif Fitriyani, Muhammad Syafrudin, Nur Chamidah, Marisa Rifada, Hendri Susilo, Dursun Aydin, Syifa Latif Qolbiyani, Seung Won Lee

“…This research presents a novel prediction model for CVDs utilizing a bagging algorithm that incorporates histogram gradient boosting as the estimator. …”
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A state-of-the-art novel approach to predict potato crop coefficient (Kc) by integrating advanced machine learning tools by Saad Javed Cheema, Masoud Karbasi, Gurjit S. Randhawa, Suqi Liu, Travis J. Esau, Kuljeet Singh Grewal, Farhat Abbas, Qamar Uz Zaman, Aitazaz A. Farooque

“…A machine learning approach using XGBoost, optimized with the Chaos Game algorithm (CGO-XGBoost), was employed to predict Kc. …”
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Wireless Sensor Networks Focusing on Predicting Average Localization Error through Machine Learning Applications by Ioanna Gounari, Mattheos Kanzilieris

“…This research offers valuable insights into the effectiveness of different ML algorithms for predicting ALE in WSNs. By demonstrating the superior performance of DTRT, the study guides practitioners and researchers in selecting models that enhance localization accuracy, ultimately improving the overall functionality of WSNs.…”
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Enhancing MPPT optimization with hybrid predictive control and adaptive P&O for better efficiency and power quality in PV systems by Benabdallah Naima, Belabbas Belkacem, Tahri Ahmed, Habib Benbouhenni, Bouddou Riyadh, Heroual Samira, Zaidi Sarra, Z. M. S. Elbarbary, Salman Arafath Mohammed

Subjects: “…Modified finite control set model predictive control…”
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Experimental Application of Predictive Controllers by C. H. F. Silva, H. M. Henrique, L. C. Oliveira-Lopes

“…The classical algorithms Infinite Horizon Model Predictive Control (IHMPC) and Model Predictive Control with Reference System (RSMPC) were used for the experimental application in the multivariable control of the pilot plant (level and pH). …”
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Development of a Novel Real-Time Weighted Surrogate Model for Wind Turbine-Based on DFIG: Enhancing Computational Efficiency in Power Systems With Error Bound by Muhammad Latif, Hira Ambreen, Tang Diyin, Farrukh Hassan, Muhammad Imran, Saddam Hussain Abbasi, Muhammad Imran

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High-order Sliding Mode Control of a Bioreactor Model through Non-Commensurate Fractional Equations by Fatemeh Saeedizadeh, Naser Pariz, Seyyed Abed Hosseini

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Low‐rank isomap algorithm by Eysan Mehrbani, Mohammad Hossein Kahaei

“…Abstract Isomap is a well‐known nonlinear dimensionality reduction method that highly suffers from computational complexity. …”
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