Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

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Enhanced Multi-Model Deep Learning for Rapid and Precise Diagnosis of Pulmonary Diseases Using Chest X-Ray Imaging by Rahul Kumar, Cheng-Tang Pan, Yi-Min Lin, Shiue Yow-Ling, Ting-Sheng Chung, Uyanahewa Gamage Shashini Janesha

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Accelerating multi-objective optimization of concrete thin shell structures using graph-constrained GANs and NSGA-II by Zhichun Fang, Xiuhong Wang, Yuyong Sun, M. A. Adibhashimi

“…The hybrid approach addresses fundamental limitations in current optimization techniques by combining the generative capabilities of deep learning with the refinement processes of evolutionary algorithms. …”
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Gaussian barebone mechanism and wormhole strategy enhanced moth flame optimization for global optimization and medical diagnostics. by Jingjing Ma, Zhifang Zhao, Lin Zhang

“…Moth Flame Optimization (MFO) is a swarm intelligence algorithm inspired by the nocturnal flight mode of moths, and it has been widely used in various fields due to its simple structure and high optimization efficiency. …”
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Dynamic parking space allocation at urban scale: Problem formulation and resolution by Hanae Errousso, Jihane El Ouadi, El Arbi Abdellaoui Alaoui, Siham Benhadou

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Nonlinear Narrowband Active Noise Control for Tractors Based on a Momentum-Enhanced Volterra Filter by Tao Zhang, Zhixuan Guan, Shuai Zhang, Kai Song, Boyan Huang

“…To address this challenge, this paper proposes a momentum-enhanced Volterra filter-based active noise control (ANC) algorithm that improves both the modeling capability of nonlinear acoustic paths and the convergence performance of the system. …”
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Optimal Design of Integrating Two‐Level Artificial Intelligent With Three Degrees of Freedom‐PDF (TLNF‐3DOFPDF) Controller for AGC of Three‐Area Multi‐Sources Power System... by Getaneh Mesfin Meseret, Rajesh Kumhar, Tarkesh Kumar Mahato, Nishant Kumar, Poonam Lakra, M. D. Mofeed Alam

“…Controller parameters are fine‐tuned using a novel metaheuristic method called the Skill Optimization Algorithm (SOA). The research assesses controller performance using multiple indices Integral of Time‐weighted Squared Error (ITSE), Integral of Squared Error (ISE), Integral of Time‐weighted Absolute Error (ITAE), and Integral of Absolute Error (IAE) and finds that ISE yields the most optimal results. …”
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An optimized system for predicting energy usage in smart grids using temporal fusion transformer and Aquila optimizer by Namdeo Baban Badhe, Rahul P. Neve, Vijaykumar P. Yele, Swati Abhang, Komal Madhukar Dhule, Darshan Mali

“…To enhance predictive performance, the Aquila Optimizer, a nature-inspired algorithm, is employed to fine-tune critical hyperparameters, ensuring optimal model convergence and performance. …”
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Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm by Fanghai Gong

“…After 231 iterations of particle swarm optimization algorithm, the optimal value is 6.83650785e-001. …”
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Integrating Digital Twin and BIM for Special-Length-Based Rebar Layout Optimization in Reinforced Concrete Construction by Daniel Darma Widjaja, Jeeyoung Lim, Sunkuk Kim

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NSGA-II-based load resource management for frequency and voltage support by Yaxin Wang, Zhihang Zhu, Zhihong Yu, Zigan Wang

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Advanced Planning Systems in Production Planning Control: An Ethical and Sustainable Perspective in Fashion Sector by Martina De Giovanni, Mariangela Lazoi, Romeo Bandinelli, Virginia Fani

“…The integration of metaheuristic algorithms—especially Ant Colony Optimization (ACO) and hybrid models like GA-ACO—further improves optimization performance by offering high-quality, near-optimal solutions without requiring extensive structural modeling. …”
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Constrained MPC for a linear system to track time-varying reference signals by Renlong WU, Nobutaka WADA

“…This paper presents a model predictive control algorithm under input and state constraints. …”
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Creating Balance on Bandwidth Consumption using Network Coding in Wireless Sensor Networks by Ehsan Kharati

“…The results show that the proposed model and algorithm, due to informed routing and NC, can improve the parameters of the average required time to find the route optimal, the total amount of virtual flow in networkâs edges, the average latency end-to-end of the network, the consumed bandwidth, the average lifetime of the network and the consumed energy, or not very weak compared to other models. …”
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Adaptive dynamic ϵ-simulated annealing algorithm for tumor immunotherapy by Xiaoyan Sun, Xiaoyan Sun, Ying Jiang

“…The algorithm is applied to an improved tumor immunotherapy model (ITIT), formulated using ordinary differential equations (ODEs) based on established experimental and clinical studies. …”
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Application of Improved Image Processing Technology in New Media Short Video Quality Improvement in Film and Television Postproduction by Yi Wang

“…In this paper, a convolutional neural network combined with a nonlinear activation function is used to establish an improved image processing technology model to efficiently extract image features. …”
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Launch dynamics modeling and simulation of box-type multiple launch rocket system considering plane clearance contact by Jinxin Tang, Guoping Wang, Genyang Wu, Yutian Sun, Lilin Gu, Xiaoting Rui

“…To quantify the contact force and friction effect between the slider and guide, the contact force model and modified Coulomb model were introduced. …”
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Blueberry Remaining Shelf-Life Prediction Based on the PSO-CNN-BiLSTM-MHA Model by Mengya Liu, Xu Cheng, Yu Cao, Qian Zhou

“…In this study, seven key features were selected from fifteen quality indicators of blueberries using the embedded method, and the PSO algorithm was used to determine the optimal hyperparameter combination of the model, which effectively improved its prediction performance. …”
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Comparative Analysis of Machine Learning and Deep Learning Models for Lung Cancer Prediction Based on Symptomatic and Lifestyle Features by Bireswar Dutta

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Investigation and application of data balancing and combined discriminant model in rock burst severity prediction by Shaohong Yan, Runze Liu, Yanbo Zhang, Xulong Yao, Yueqi Yang, Qi Wang, Bin Guo, Shuai Wang

“…Ultimately, a BO-MLP-RF composite prediction model was constructed based on Bayesian Optimization (BO), Multilayer Perceptron (MLP), and Random Forest (RF) algorithms, with the Bayesian Optimization method ensuring that the model fits the training data well and generalizes to the test data. …”
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