Improving fluoroprobe sensor performance through machine learning by D. Lafer, A. Sukenik, T. Zohary, O. Tal

“…Phytoplankton species biomass data were collected concurrently using standard inverted microscope counts. The SVR algorithm outperformed the other algorithms in predicting phytoplankton abundance and composition in Lake Kinneret, based on the FP measurements. …”
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A Novel Remote Sensing Recognition Using Modified GMM Segmentation and DenseNet by Muhammad Waqas Ahmed, Moneerah Alotaibi, Sultan Refa Alotaibi, Dina Abdulaziz Alhammadi, Asaad Algarni, Ahmad Jalal, Jeongho Cho

“…The use of optimization algorithms further enhances the discriminative power of the features, leading to improved classification accuracy.…”
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Modelling the Isotope composition of groundwater using hydrochemical properties in eastern Saudi Arabia: Implementation of innovative data intelligence techniques by Mohammed Benaafi, Waleed M. Hamanah, Ebrahim Al-Wajih

“…New hydrological insight for the region: Eight AI algorithms (KNN, SVR, RF, ET, Bag, AdaBt, GRB, and CAT) and stacking ensemble models were developed to predict the δ¹ ⁸O and δ²H isotopes of the groundwater using a dataset of physicochemical parameters, ions and elements, and isotopes from 47 wells. …”
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Identification of mitophagy-related biomarkers and immune infiltration in polycystic ovarian syndrome by bioinformatic study by Hongjuan Ye, Xicheng Wang, Zhiying He

“…The potential biomarkers of mitophagy-related and immune infiltration in PCOS were screened by protein-protein interaction network using different algorithms, and the area under the curve was calculated to analyze their diagnostic value. …”
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Comparison of Kolmogorov–Arnold Networks and Multi-Layer Perceptron for modelling and optimisation analysis of energy systems by Talha Ansar, Waqar Muhammad Ashraf

“…Considering the improved interpretable performance of Kolmogorov–Arnold Networks (KAN) algorithm compared to multi-layer perceptron (MLP) algorithm, a fundamental research question arises on how modifying the loss function of KAN affects its modelling performance for energy systems, particularly industrial-scale thermal power plants. …”
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A two‐stage reactive power optimization method for distribution networks based on a hybrid model and data‐driven approach by Ghulam Abbas, Wu Zhi, Aamir Ali

“…The computational limitations of the traditional algorithms and the development of artificial intelligence (AI) based technologies have promoted the advancement of hybrid model‐data‐driven algorithms. …”
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Forecasting mental states in schizophrenia using digital phenotyping data. by Thierry Jean, Rose Guay Hottin, Pierre Orban

“…Besides it remains unclear which machine learning algorithm is best suited for forecast tasks, the eXtreme Gradient Boosting (XGBoost) and long short-term memory (LSTM) algorithms being 2  popular choices in digital phenotyping studies. …”
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Federated Digital Twins: A Scheduling Approach Based on Temporal Graph Neural Network and Deep Reinforcement Learning by Young-Jin Kim, Hanjin Kim, Beomsu Ha, Won-Tae Kim

“…Traditional scheduling algorithms, which assume static processing speeds for machines (corresponding to DTs), encounter limitations in generating optimal schedules. …”
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AI‐Powered Multimodal Modeling of Personalized Hemodynamics in Aortic Stenosis by Caglar Ozturk, Daniel H. Pak, Luca Rosalia, Debkalpa Goswami, Mary E. Robakowski, Raymond McKay, Christopher T. Nguyen, James S. Duncan, Ellen T. Roche

“…The efficiency and reliability of these algorithms make them an ideal complementary tool for personalized high‐fidelity modeling of AS biomechanics, hemodynamics, and treatment planning.…”
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Clustering Analysis in Wireless Sensor Networks: The Ambit of Performance Metrics and Schemes Taxonomy by Asim Zeb, A. K. M. Muzahidul Islam, Mahdi Zareei, Ishtiak Al Mamoon, Nafees Mansoor, Sabariah Baharun, Yoshiaki Katayama, Shozo Komaki

“…The objective of this paper is to review and analyze the latest prominent cluster-based WSN algorithms using various measurement parameters. In this paper, unique performance metrics are designed which efficiently evaluate prominent clustering schemes. …”
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Motion feature extraction using magnocellular-inspired spiking neural networks for drone detection by Jiayi Zheng, Jiayi Zheng, Yaping Wan, Xin Yang, Hua Zhong, Minghua Du, Gang Wang, Gang Wang

“…Experimental results in terms of drone detection performance indicate that the incorporation of MG-SNN significantly improves the accuracy of low-altitude drone detection tasks compared to popular small object detection algorithms, acting as a cheap plug-and-play module in detecting small flying targets against complex backgrounds.…”
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Prevalence, comorbidities, and disease-related complications of rheumatoid arthritis in Colombia: a national cross-sectional study based on administrative claims data by Kevin Maldonado-Cañón, Giancarlo Buitrago, Gerardo Quintana-López

“…We used a set of sensitive and specific electronic algorithms (i.e., a set of rules) applied to linked data based on ICD-10 codes and unique medication use codes. …”
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SYMBOLIC ANALYSIS OF CLASSICAL NEURAL NETWORKS FOR DEEP LEARNING by Vladimir Milićević, Igor Franc, Maja Lutovac Banduka, Nemanja Zdravković, Nikola Dimitrijević

“…This unique original method can help scientists and programmers design complex machine learning algorithms and understand how deep learning algorithms work. …”
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The method of increasing the efficiency of the man-machine system functioning by improving the quality of decision support system software by О.В. Турінський, М.А. Павленко, Г.В. Пєвцов, С.В. Осієвський

“…The time complexity of the algorithms implementing the relevance tree tasks was evaluated. …”
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Multiplex Community Detection in Social Networks Using a Chaos-Based Hybrid Evolutionary Approach by Bagher Zarei, Bahman Arasteh, Mehdi Asadi, Vahid Majidnezhad, Saeid Taghavi Afshord, Asgarali Bouyer

“…This makes the algorithm converge faster. (b) A dedicated local search is employed at the end of each cycle of the algorithm. …”
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Peptide-Based Vaccinology: Experimental and Computational Approaches to Target Hypervariable Viruses through the Fine Characterization of Protective Epitopes Recognized by Monoclon... by Matteo Castelli, Francesca Cappelletti, Roberta Antonia Diotti, Giuseppe Sautto, Elena Criscuolo, Matteo Dal Peraro, Nicola Clementi

“…Thus, in the last decade many epitope predictive algorithms have been developed. These algorithms are continually evolving, and their use to address the empirical research is widely increasing. …”
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Qualitative Discrimination of Intact Tobacco Leaves Based on Near-Infrared Technology by Mengyao Lu, Qiang Zhou, Tian’en Chen, Junhui Li, Shuwen Jiang, Qin Gao, Cong Wang, Dong Chen

“…The spectral characteristics and spectral preprocessing methods of intact tobacco leaves are analyzed, and then different spectra (independent or average spectra) and different algorithms (discriminant partial least-squares (DPLS) and Fisher’s discriminant algorithms) are used to construct discriminant models for verifying the feasibility of intact leaf modeling and determining the optimal model conditions. …”
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Improved Binary Grey Wolf Optimization Approaches for Feature Selection Optimization by Jomana Yousef Khaseeb, Arabi Keshk, Anas Youssef

“…A set of comparisons were made against the original binary versions of both GWO and PSO algorithms and against eight state-of-the-art feature selection binary optimizers in addition to one of the recent binary optimizers that combines PSO with GWO. …”
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3D Semantic VSLAM of Indoor Environment Based on Mask Scoring RCNN by Chongben Tao, Yufeng Jin, Feng Cao, Zufeng Zhang, Chunguang Li, Hanwen Gao

“…This paper proposed a 3D semantic VSLAM algorithm called BMASK-RCNN based on Mask Scoring RCNN. …”
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AIR-POLSAR-CR1.0: A Benchmark Dataset for Cloud Removal in High-Resolution Optical Remote Sensing Images with Fully Polarized SAR by Yuxi Wang, Wenjuan Zhang, Jie Pan, Wen Jiang, Fangyan Yuan, Bo Zhang, Xijuan Yue, Bing Zhang

“…In summary, AIR-POLSAR-CR1.0 fills the gap in polarization feature images and demonstrates good adaptability for the development of deep learning algorithms.…”
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