Optimal Distributed Dispatch of Smart Multi-Agent Energy Hubs Based on Consensus Algorithm Considering Lossy Communication Network and Uncertainty by Abdelfattah A. Eladl, Magda I. El-Afifi, Magdi M. El-Saadawi, Bishoy E. Sedhom

“…Two case studies are applied to explain performance and effectiveness of the proposed algorithm with different packet loss scenarios. Under uncertainty, sensitivity of the system was evaluated. …”
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Algorithm to assess neutron HP(10) with estimation of uncertainties using Alnor albedo dosemeters: application in Brazilian nuclear power plants by Max da Silva Ferreira, Everton Rodrigues Silva, Cláudia Lúcia de Pinho Maurício

“…This study proposes an algorithm for evaluating the photons and neutrons HP(10) values for the Alnor albedo system. …”
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Optimizing Autonomous Multi-UAV Path Planning for Inspection Missions: A Comparative Study of Genetic and Stochastic Hill Climbing Algorithms by Faten Aljalaud, Yousef Alohali

“…Efficient path planning is vital for multi-UAV inspection missions, yet the comparative effectiveness of different optimization strategies has not received much attention. …”
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Extreme gradient and boosting algorithm for improved bias-correction and downscaling of CMIP6 GCM data across indian river basin by Chandni Thakur, Venkatesh Budamala, KS Kasiviswanathan, Claudia Teutschbein, Bankaru-Swamy Soundharajan

“…Additionally, both methods were evaluated across different seasons, including monsoon, pre-monsoon, and post-monsoon. …”
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A comparative study of four deep learning algorithms for predicting tree stem radius measured by dendrometer: A case study by Guilherme Cassales, Serajis Salekin, Nick Lim, Dean Meason, Albert Bifet, Bernhard Pfahringer, Eibe Frank

“…In this study, we aimed to evaluate four Deep Learning algorithms (namely CNN, LSTM, Transformer, and ETSFormer), using automatically measured and high temporal resolution tree stem radius data. …”
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Enhanced NSGA-II algorithm based on novel hybrid crossover operator to optimise water supply and ecology of Fenhe reservoir operation by Qinglai Xiong, Ling Dong, Hu Chen, Xueping Zhu, Xuehua Zhao, Xuerui Gao

“…A comparative analysis of the bi-objective optimisation schemes obtained using different crossover operators indicates the following: (1) the NSGA-II algorithm based on the SBAX operator achieves a convergence efficiency that is 14.25–41.95% higher than that of the conventional NSGA-II algorithm; (2) the reservoir operation indices of the scheduling scheme derived from the NSGA-II algorithm based on the SBAX operator significantly outperform those obtained using the conventional NSGA-II algorithm. …”
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Using a seasonal and trend decomposition algorithm to improve machine learning prediction of inflow from the Yellow River, China, into the sea by Shuo Wang, Shuo Wang, Ke Yang, Ke Yang, Hui Peng, Hui Peng

“…In this study, the inflow from the Yellow River into the sea was predicted based on a machine learning model (light gradient boosting machine, LightGBM) and a time decomposition algorithm (seasonal and trend decomposition using loess, STL), and the future data leakage in different ways of using STL were evaluated. …”
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Synergistic hyperspectral and SAR imagery retrieval of mangrove leaf area index using adaptive ensemble learning and deep learning algorithms by Jun Sun, Weiguo Jiang, Bolin Fu, Hang Yao, Huajian Li

“…This study proposes a new approach to the retrieval of the mangrove LAI by combining a one-dimensional convolutional neural network (1D-CNN) with adaptive ensemble learning regression (AELR) and deep learning regression (DNNR) algorithms. We further evaluated the performance of OHS (Zhuhai-1) hyperspectral and GF-3 SAR images in mapping the spatial distribution of the LAI in mangroves. …”
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Estimating ocean currents from the joint reconstruction of absolute dynamic topography and sea surface temperature through deep learning algorithms by D. Ciani, C. Fanelli, B. Buongiorno Nardelli

“…Retrieving consistent high-resolution ADT and SST information from space is challenging, due to instrument limitations, sampling constraints, and degradations introduced by the interpolation algorithms used to obtain gap-free (L4) analyses. To address these issues, we developed and tested different deep learning methodologies, specifically convolutional neural network (CNN) models that were originally proposed for single-image super resolution. …”
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Application of machine learning algorithms for predicting the life-long physiological effects of zinc oxide Micro/Nano particles on Carum copticum by Maryam Mazaheri-Tirani, Soleyman Dayani, Majid Iranpour Mobarakeh

“…In this study, nine ML algorithms [Support-Vector Regression (SVR), Linear, Bagging, Stochastic Gradient Descent (SGD), Gaussian Process, Random Sample Consensus (RANSAC), Partial Least Squares (PLS), Kernel Ridge, and Random Forest] were applied to evaluate their efficiency in predicting the effects of zinc oxide nanoparticles (ZnO NPs: 0.5, 1, 5, 25, and 125 µM) and microparticles (ZnO MPs: 1, 5, 25, and 125 µM) on Carum copticum. …”
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Genetic algorithm optimization of ensemble learning approach for improved land cover and land use mapping: Application to Talassemtane National Park by Ali Azedou, Aouatif Amine, Isaya Kisekka, Said Lahssini

“…This study proposes a Genetic Algorithm (GA) optimization method for ensemble classification to improve LCLU classification accuracy while maintaining computational efficiency. …”
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Exploration of the Ignition Delay Time of RP-3 Fuel Using the Artificial Bee Colony Algorithm in a Machine Learning Framework by Wenbo Liu, Zhirui Liu, Hongan Ma

“…Ignition delay time (IDT) is a critical parameter for evaluating the autoignition characteristics of aviation fuels. …”
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Assessment of Spectral Computed Tomography Image Quality and Detection of Lesions in the Liver Based on Image Reconstruction Algorithms and Virtual Tube Voltage by Areej Hamami, Mohammad Aljamal, Nora Almuqbil, Mohammad Al-Harbi, Zuhal Y. Hamd

“…<b>Objectives</b>: This study evaluated improvements in image quality achieved using various virtual tube voltages and reconstruction algorithms for diagnosing common liver diseases with spectral CT. …”
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Performance evaluation of primary user and secondary user based on CSMA protocol in CRSN by Ying LIU, Li ZHENG, Yuansong LI

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Performance evaluation of primary user and secondary user based on CSMA protocol in CRSN by Ying LIU, Li ZHENG, Yuansong LI

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EVALUATION OF MACHINE LEARNING MODELS FOR BORON PREDICTION IN ANDISOL SOILS OF NARIÑO-COLOMBIA by David Álvarez Sánchez, Xilena López Estrella, Eduar Manso Ordoñez, Laura López Rivera, Jeison Rodriguez Valenzuela

“…To explore the application of ML tools for the prediction of Boron levels in Andisols soils of Nariño has been explored and identifying the most efficient algorithm. Methodology. A total of 1,067 soil samples collected in various fields of five municipalities in the southern subregion of the department were used, where the supervised learning models, Random Forest (RF), K-Nearest Neighbors (K-NN), Support Vector Machine (SVM) and Naive Bayes (NB) were evaluated. …”
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Evaluation of the effectiveness of defense measures during radiological risk assessment in gynecological brachytherapy by C. C. Dominguez, A. Torres, R. Alfonso

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The dosimetric impacts of ct-based deep learning autocontouring algorithm for prostate cancer radiotherapy planning dosimetric accuracy of DirectORGANS by Serap Çatlı Dinç, Aybala Nur Üçgül, Hüseyin Bora, Ertuğrul Şentürk

“…Abstract Purpose In study, we aimed to dosimetrically evaluate the usability of a new generation autocontouring algorithm (DirectORGANS) that automatically identifies organs and contours them directly in the computed tomography (CT) simulator before creating prostate radiotherapy plans. …”
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Raman and FT-IR Spectroscopy Coupled with Machine Learning for the Discrimination of Different Vegetable Crop Seed Varieties by Stefan M. Kolašinac, Marko Mladenović, Ilinka Pećinar, Ivan Šoštarić, Viktor Nedović, Vladimir Miladinović, Zora P. Dajić Stevanović

“…The aim of this research is to investigate the potential of Raman and FT-IR spectroscopy as well as mathematical linear and non-linear models as a tool for the discrimination of different seed varieties of paprika, tomato, and lettuce species. …”
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Performance evaluation of perceptible impulsive noise detection methods based on auditory models by Arda Özdoğru, František Rund, Karel Fliegel

“…Evaluation criteria of the algorithms included the hit rate, false alarm rate, $$A'$$ A ′ , and computational time. …”
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