Metaparameter optimized hybrid deep learning model for next generation cybersecurity in software defined networking environment by C. Labesh Kumar, Suresh Betam, Denis Pustokhin, E. Laxmi Lydia, Kanchan Bala, Rajanikanth Aluvalu, Bhawani Sankar Panigrahi

“…Furthermore, the binary narwhal optimizer (BNO)-based feature selection is accomplished to classify the most related features. …”
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FLIP: A Novel Feedback Learning-Based Intelligent Plugin Towards Accuracy Enhancement of Chinese OCR by Xinyue Tao, Yueyue Han, Yakai Jin, Yunzhi Wu

“…This study develops FLIP (Feedback Learning-based Intelligent Plugin), a lightweight post-processing plugin designed to improve Chinese OCR accuracy across different systems without external dependencies. …”
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Modern approaches to the diagnosis and treatment of cardiac sarcoidosis: results of a cohort study by S. V. Mairina, D. V. Ryzhkova, L. B. Mitrofanova, A. V. Ryzhkov, P. M. Murtazalieva, O. M. Moiseeva

“…All patients underwent 18F-fluorodeoxyglucose positron emission tomography (PET).Results. The most common (53%) electrocardiographic abnormality was right bundle branch block. …”
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Small-Signal Stability Analysis and Parameters Optimization of Virtual Synchronous Generator for Low-Inertia Power System by Alaa Altawallbeh, Abdulrahman Alassi, Nader Meskin, Mohammed A. Al-Hitmi, Ahmed M. Massoud

“…We further propose a hybrid Particle Swarm Optimization (PSO) algorithm with a multi-objective cost function to optimize VSG controller gains. …”
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A stochastic optimization method for economic microgrid operation based on "source-load operation" mode classification by ZHOU Hang, MA Lihong, LI Zhongzhong, WANG Haisheng, LI Sifan, ZHANG Changjun, FU Linbei

“…First， a multivariate time series representation based on information granules is used， and the traditional affinity propagation （AP） is improved with spatial weighted matrix distance （SWMD）. …”
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Comparative Study on Hyperparameter Tuning for Predicting Concrete Compressive Strength by Jeonghyun Kim, Donwoo Lee

“…This study assesses the impact of hyperparameter optimization algorithms on the performance of machine learning-based concrete compressive strength prediction models. …”
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Modern possibilities for optimizing the calculation of intraocular lens optical power using deep machine learning capabilities by A.R. Vinogradov, B.G. Dzhashi, S.V. Balalin

“…The development of a software application based on artificial intelligence is a rather labor-intensive process that requires processing a large amount of data, using formulas and algorithms with obtaining the final result, as well as subsequent training, optimization, and improving the quality of its work. …”
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Parameter Sensitivity Analysis and Irrigation Regime Optimization for Jujube Trees in Arid Regions Using the WOFOST Model by Shihao Sun, Yingjie Ma, Pengrui Ai, Ming Hong, Zhenghu Ma

“…The subsequent multi-objective optimization of yield and crop water productivity of dates under different combinations of water and potassium treatments under a bi-objective optimization model based on the NSGA-II algorithm showed that the optimal strategy was irrigation at 80% ET_c combined with 300 kg/ha of potassium application. …”
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Deep Reinforcement Learning-Based Two-Phase Hybrid Optimization for Scheduling Agile Earth Observation Satellites by Guanghui Zhou, Zhicheng Jin, Dongning Liu

“…The experimental results demonstrate that the TPHO framework with MRC rules achieves superior performance, yielding a total reward improvement exceeding 16% compared with the A-ALNS algorithm in the most complex scenario involving 1200 tasks, yet requiring less than 3% of the computational duration of A-ALNS.…”
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RM-MOCO: A Fast-Solving Model for Neural Multi-Objective Combinatorial Optimization Based on Retention by Huiqing Wei, Fei Han, Qing Liu, Henry Han

“…Recently, learning-based methods have achieved good results in solving MOCO problems. However, most of these methods use attention mechanisms and their variants, which have room for further improvement in the speed of solving MOCO problems. …”
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Design and Multi-Objective Optimization of Auxetic Sandwich Panels for Blastworthy Structures Using Machine Learning Method by Andika, Sigit Puji Santosa, Djarot Widagdo, Arief Nur Pratomo

“…The optimization results show significant improvements in blastworthiness performance, with notable reductions in permanent displacement and enhancements in specific energy absorption (SEA). …”
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AI-Based Classification Model for Low-Energy Buildings: Promoting Sustainable Economic Development of Smart Cities With Spherical Fuzzy Decision Algorithm by Lin Yang

“…AI-based classification models for low-energy buildings are essential in promoting the economic development of smart cities by optimizing energy use, reducing operational costs, and enhancing overall efficiency. …”
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A comprehensive review on the integration of artificial intelligence in friction stir welding for monitoring, modelling, and process optimization by Mostafa Akbari, Ezatollah Hassanzadeh, Yaghuob Dadgar Asl, Amirhossein Moghanian

“…Lastly, the third section pertains to the optimization of FSW parameters, illustrating how AI-driven algorithms analyze complex interactions among multiple variables to determine the most effective process settings. …”
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Path planning of unmanned ships based on A* and dynamic window approach by FU Long, SHEN Zhen, TAO Hao, HAN Yunjun, DONG Xisong, XIONG Gang

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Optimization of PV parameters under varied environmental conditions: A hybrid secant–Newton-Raphson method by Brahim El Fahmi, Driss Saadaoui, Imade Choulli, Khalid Assalaou, Ismail Abazine, Mustapha Elyaqouti, El hanafi Arjdal, Mohammed Agdam, Yassine El aidi Idrissi

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Algorithm for assigning different 6-month short-term chemotherapy regimens in patients with drug-resistant tuberculosis: how to make the right choice for the clinician by Yu.I. Feshchenko, N.A. Lytvynenko, L.M. Protsyk, M.V. Pohrebna, Yu.O. Senko

“…For patients with pre-XDR-TB, the BPaL regimen offers the best balance of efficacy, tolerability, and cost-effectiveness. The proposed prescription algorithms enable a personalized treatment approach and improve therapeutic outcomes.…”
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6G virtualized beamforming: a novel framework for optimizing massive MIMO in 6G networks by Ahmed M. Alwakeel

“…Our framework employs a combination of advanced machine learning algorithms and software-defined networking to dynamically allocate beamforming resources, improving adaptability in high-density environments and optimizing signal-to-noise ratios. …”
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A deep neural network approach for optimizing charging behavior for electric vehicle ride-hailing fleet by Kaizhe Chen, Jin Liu, Wenjing Lyu, Tianyuan Wang, Jinxi Wen

“…Therefore, this research develops a Neural Network (NN) trained with the Adaptive Moment Estimation (Adam) algorithm, based on 2.14 million charging events. The goal is to analyze current charging behaviors and evaluate the impact of key variables on costs and emissions, providing data-driven insights for potential improvements, thus addressing a critical research gap. …”
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Optimizing precision farming: enhancing machine learning efficiency with robust regression techniques in high-dimensional data by Nour Hamad Abu Afouna, Majid Khan Majahar Ali

“… Smart precision farming leverages IoT, cloud computing, and big data to optimize agricultural productivity, lower costs, and promote sustainability through digitalization and intelligent methodologies. …”
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Artificial Intelligence and MCDA in Circular Economy: Governance Strategies and Optimization for Reverse Supply Chains of Solid Waste by Joel Joaquim de Santana Filho, Arminda do Paço, Pedro Dinis Gaspar

“…The results indicate that hybrid MCDA-AI models, employing techniques, such as TOPSIS, AHP, neural networks, and genetic algorithms, enhance decision-making automation, reduce costs, and improve waste traceability. …”
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