A Novel Evolutionary Deep Learning Approach for PM_2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran by Mehrdad Kaveh, Mohammad Saadi Mesgari, Masoud Kaveh

“…To overcome these issues, we propose integrating the novel orchard algorithm (OA) with LSTM to optimize air pollution forecasting. …”
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Single-Glazed Vacuum Tube Collector with SnAl₂O₃ Selective Flat Absorber Plate and Gravity Single-Stage Direct Water Flow: A Comprehensive Geometric Optimizat... by Aleksandar Nešović, Robert Kowalik

“…The thermal performance with the geometric optimization (absorber width and glass tube thickness) of the presented solar collector type was determined using the specially designed iterative calculation algorithm (phase 1) and the double multi-criteria analysis (phase 2). …”
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Optional and mandatory assignment strategies for dynamic vehicle routing with time windows by Mustafa Demirbilek

“…In MPA, customer requests can be rejected if future requests are expected to be more advantageous, whereas MPM mandates accepting requests provided vehicle capacity is sufficient. After optimizing the methods through sensitivity analyses, we evaluated their performance against Clarke and Wright's Savings Algorithm (CW) across various real-world-inspired scenarios, including different time window lengths, interarrival times, and region types. …”
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Physics-Informed Decoupled Calibration for Fourier Ptychographic Microscopy by Mingdi Liu, Junzhao Liang, Yanxiong Wu, Zicong Luo, Rui Xie, Jiaxiong Luo, Lisong Yan

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Dynamic control of a 10 MW solar-autothermal hybrid biomass gasifier for round-the-clock processing with stable syngas production by Axel Curcio, Sylvain Rodat, Valéry Vuillerme, Stéphane Abanades

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High-Performance Identification and Control of MIMO (Multiple Input—Multiple Output) Experimental Module with Fractional-Order Approach Application by Alexandre Marques de Almeida, Alisson Luan Daga, Rafael Palma Setti Penteado Lanzarini, Ervin Kaminski Lenzi, Marcelo Kaminski Lenzi

“…An important aspect concerns the use of Particle Swarm Optimization (PSO) metaheuristic algorithm for optimization tasks, both in parameter estimation and controller tuning. …”
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From Land Conservation to Famers’ Income Growth: How Advanced Livelihoods Moderate the Income-Increasing Effect of Land Resources in an Ecological Function Area by Xinyu Zhang, Yiqi Zhang, Yanjing Yang, Wenduo Wang, Xueting Zeng

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AutoML: A systematic review on automated machine learning with neural architecture search by Imrus Salehin, Md. Shamiul Islam, Pritom Saha, S.M. Noman, Azra Tuni, Md. Mehedi Hasan, Md. Abu Baten

“…AutoML emerged to increase productivity and efficiency by automating as much as possible the inefficient work that occurs while repeating this process whenever machine learning is applied. …”
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An Enhanced Fractional Open Circuit Voltage MPPT Method for Rapid and Precise MPP Tracking in Standalone Photovoltaic Systems by Muhannad J. Alshareef

“…Instead of focusing solely on individual optimization MPPT algorithms, current studies now explore combining different methods for better results. …”
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Reliability Estimation for the Gull Alpha Power Pareto Model Under Progressive Type-I Censoring by Mahmoud M. Abdelwahab, Ahmed R. El-Saeed, M. A. Abdelkawy, Mohamed Khalifa Ahmed Issa, Hanem Mohamed

“…Estimation methods were investigated from an algorithmic perspective: for maximum likelihood estimation, the Newton-Raphson algorithm was adapted, while for Bayesian estimation, Markov Chain Monte Carlo methods were employed, utilizing the Metropolis-Hastings algorithm. …”
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A trade-off between line hardening and dynamic line rating by a new convex optimization model for resilient micro-grid-oriented expansion planning of reconfigurable smart distribut... by Saeed Behzadi, Amir Bagheri

“…The simulation results demonstrate the efficacy of the conducted model. According to the optimal Pareto algorithm solution, the resiliency index is guaranteed to be more than 92% in the face of LPHI disasters. …”
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The Hydrodynamic Performance of a Vertical-Axis Hydro Turbine with an Airfoil Designed Based on the Outline of a Sailfish by Aiping Wu, Shiming Wang, Chenglin Ding

“…Through Latin hypercube experimental design combined with optimization algorithms, four key geometric variables governing the airfoil’s hydrodynamic characteristics were systematically analyzed. …”
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An Innovative Smart Irrigation Using Embedded and Regression-Based Machine Learning Technologies for Improving Water Security and Sustainability by Abdennabi Morchid, Abdennacer Elbasri, Zahra Oughannou, Hassan Qjidaa, Rachid El Alami, Badre Bossoufi, Saleh Mobayen, Pawel Skruch

“…This study proposes an irrigation system based on embedded systems, using sensors and algorithms to collect and analyze data in order to optimize water management. …”
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Comparative Analysis of Traditional and Deep Learning Approaches for Underwater Remote Sensing Image Enhancement: A Quantitative Study by Yunsheng Ma, Yanan Cheng, Dapeng Zhang

“…This study compares a multi-scale fusion-enhanced physical model and deep learning algorithms to optimize intelligent processing. The physical model, based on the Jaffe–McGlamery model, integrates multi-scale histogram equalization, wavelength compensation, and Laplacian sharpening, using cluster analysis to target enhancements. …”
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Three-Dimensional Shape Reconstruction from Digital Freehand Design Sketching Based on Deep Learning Techniques by Ding Zhou, Guohua Wei, Xiaojun Yuan

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A Consensus-Driven Distributed Moving Horizon Estimation Approach for Target Detection Within Unmanned Aerial Vehicle Formations in Rescue Operations by Salvatore Rosario Bassolillo, Egidio D’Amato, Immacolata Notaro

“…It provides a fully distributed architecture that enables UAVs to estimate the position and velocity of other fleet members while simultaneously detecting static and dynamic targets. …”
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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…Subsequently, both classical and quantum-inspired models are trained and optimized. The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
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Expedited re-design of multi-band passive microwave circuits using orthogonal scaling directions and gradient-based tuning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Ubaid Ullah

“…In particular, the employment of a given passive structure in a different application area often requires re-adjustment of the operating frequencies/bands while maintaining top performance. Achieving this necessitates the utilization of numerical optimization methods. …”
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Techno-economic analysis and energy management strategies for micro gas turbines: A state-of-the-art review by A.H. Samitha Weerakoon, Mohsen Assadi

“…Additionally, the optimization of Micro Gas Turbine systems using advanced algorithms enhances energy efficiency by 10–15%, highlighting the importance of smart control systems and optimal component sizing. …”
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Sparse support path generation for multi-axis curved layer fused filament fabrication by Tak Yu Lau, Dong He, Yamin Li, Yihe Wang, Danjie Bi, Lulu Huang, Pengcheng Hu, Kai Tang

“…Firstly, the overhang regions are detected by identifying the overhang points given a multi-axis nozzle path. Then, an optimization framework for the support guide curve is proposed to minimize its total length while ensuring that overhang filaments can be stably supported. …”
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