Parametric optimization of the slot waveguide characteristics using a machine-learning approach by Yadvendra Singh, Suraj Jena, Harish Subbaraman

“…Thus, providing a useful ML methodology for efficient optimization of slot waveguide structures for future applications.…”
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Design and application research of traditional Chinese medicine teaching resource recommendation system based on multivariate data mining driven algorithm by Wei Zhang, Yaqing Liu, Qiang Zhang, Xiaomin Chen

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BSDR: A Data-Efficient Deep Learning-Based Hyperspectral Band Selection Algorithm Using Discrete Relaxation by Mohammad Rahman, Shyh Wei Teng, Manzur Murshed, Manoranjan Paul, David Brennan

“…Hyperspectral band selection algorithms are crucial for processing high-dimensional data, which enables dimensionality reduction, improves data analysis, and enhances computational efficiency. …”
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Nature inspired optimization of IoT network for delay resistant and energy efficient applications by Gagandeep Kaur, Vipin Balyan, Sindhu Hak Gupta

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Preference-based expensive multi-objective optimization without using an ideal point by Peipei Zhao, Liping Wang, Qicang Qiu

“…Abstract As a decision maker is not always interested in the entire Pareto front, a natural idea is to take into account user preferences in computationally expensive multi-objective optimization to focus on searching the preferred region. …”
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An Enhanced Comprehensive Learning Particle Swarm Optimizer with the Elite-Based Dominance Scheme by Chengcheng Chen, Xianchang Wang, Helong Yu, Nannan Zhao, Mingjing Wang, Huiling Chen

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An optimized multi-task contrastive learning framework for HIFU lesion detection and segmentation by Matineh Zavar, Hamid Reza Ghaffari, Hamid Tabatabaee

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RL-BES: optimizing strategies using reinforcement learning for blockchain economic security by Erdeng Wen, Zhuotao Deng, Yifan Mo, Yuren Zhou, Xiaohong Shi

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The Algorithm for Preparing a Set of Data for Teaching Neural Networks on the Example of the Task to Analyze the Radiological Images of Lungs by A. A. Kosareva

“…The influence of the stages (marking of images, normalization of data, determining the dynamic image range, the composition of the training sample) of the algorithm for the learning result is evaluated. The greatest influence in solving the task of modality verification of modality was the choice of optimal values of the dynamic range. …”
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An improved multi-strategy equilibrium optimizer for surface marine vehicle path planning by Jianguo Yu, Yanyang Lu, Hamid Reza Karimi, Derong Zhu, Bin Li, Yiming Wang

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Integrating Machine Learning and Multi-Objective Optimization in Biofuel Systems: A Review by Ivan P. Malashin, Dmitry A. Martysyuk, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…This review synthesizes key advancements in biofuel optimization, highlighting the use of techniques such as Artificial Neural Networks (ANN), Genetic Algorithms (GA), Non-Dominated Sorting Genetic Algorithm II (NSGA-II), and Response Surface Methodology (RSM). …”
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Optimizing Fairness and Spectral Efficiency With Shapley-Based User Prioritization in Semantic Communication by Moirangthem Tiken Singh, Adnan Arif, Rabinder Kumar Prasad, Bikramjit Choudhury, Chandan Kalita, Sikdar Md. S. Askari

“…The Shapley-based approach outperforms established methods, including the Hungarian algorithm, reinforcement learning algorithms like Deep Q-Network (DQN) and Proximal Policy Optimization (PPO), as well as conventional 4G and 5G resource allocation strategies. …”
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Hybrid Model for 6G Network Traffic Prediction and Wireless Resource Optimization by Mohammed Anis Oukebdane, A. F. M. Shahen Shah, Md Baharul Islam, John Ekoru, Milka Madahana

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Optimizing skin cancer screening with convolutional neural networks in smart healthcare systems. by Ali Raza, Akhtar Ali, Sami Ullah, Yasir Nadeem Anjum, Basit Rehman

“…In this researche new activation function namely NGNDG-AF was offered specifically to enhance the capabilities of network fitting and generalization ability, convergence rate and reduction in mathematical computational cost. A research used an optimized CNN and ResNet152V2 with the HAM10000 dataset to differentiate between the seven forms of skin cancer. …”
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Application of Machine Learning Models in Optimizing Wastewater Treatment Processes: A Review by Florin-Stefan Zamfir, Madalina Carbureanu, Sanda Florentina Mihalache

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Optimizing mRNA Vaccine Degradation Prediction via Penalized Dropout Approaches by Hwai Ing Soon, Azian Azamimi Abdullah, Hiromitsu Nishizaki, Latifah Munirah Kamarudin

“…A novel tetramer-label encoding approach (4-mer-lbA) was proposed, integrating biological relevance with data-driven analysis to enhance predictive accuracy. To further optimize model performance, two advanced hyperparameter optimization (HPO) techniques—Dropout-Enhanced Technique (DEet) and Hyperparameter Optimization Algorithm Penalizer (HOPeR)—are proposed to mitigate overfitting, address inefficiencies in conventional HPO algorithms (HPOAs), and accelerate model convergence. …”
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Exploration and Exploitation Mechanism in Pairwise Test Case Generation: A Systematic Literature Review by Muhammad Sabo Yahaya, Ahmad Sobri B. Hashim, Abdullateef Oluwagbemiga Balogun, Aminu Aminu Muazu, Fatima Sabo Usman, Dahiru Adamu Aliyu, Abdullahi Uwaisu Muhammad

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Revolutionizing FANETs With Reinforcement Learning: Optimized Data Forwarding and Real-Time Adaptability by Yasir Ibraheem Mohammed, Rosilah Hassan, Mohammad Kamrul Hasan, Shayla Islam, Huda Saleh Abbas, Muhammad Asghar Khan, Muhammad Attique Khan

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An experimental optimization environment for developing an intracycle pitch control in cross flow turbines by Stefan Hoerner, Roberto Leidhold, Shokoofeh Abbaszadeh, Karla Ruiz-Hussmann, Timo Bennecke, Zhao Zhao, Paul Joedecke, Christian-Thoralf Weber, Pierre-Luc Delafin, Cyrille Bonamy, Yves Delannoy

“…A superimposed governing system performs an experimental optimization process. Evolutionary algorithms are to be employed to solve two objectives: (1) maximizing the efficiency and (2) minimizing the structural loads. …”
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Elaboration of the Calculation Algorithm for the Load Diagram of a Thermoelectric Generator that Applies the Temperature Dependent Thermoelectric Layer Properties by Golubev R.O., Stolyarov S.P.

“…The specific power calculation allows defining the performance per a cross-sectional unit area. The optimal selection of variables reduces the computational time. …”
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