Pricing principles in the field of ready–made meal delivery: analysis of influence factors by K. V. Martynov

“…The study describes the most popular pricing principles: cost–based, competitor–oriented, as well as dynamic algorithms taking into account seasonal demand. The results reflecting the willingness of customers to pay extra while observing short delivery times and maintaining product quality are studied. …”
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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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Reconceptualizing Gatekeeping in the Age of Artificial Intelligence: A Theoretical Exploration of Artificial Intelligence-Driven News Curation and Automated Journalism by Dan Valeriu Voinea

“…Simultaneously, automated news generation via LLMs raises questions about how training data and optimization goals (engagement vs. diversity) act as new “<i>gatekeepers</i>” in story selection and framing. …”
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Machine learning-aided hybrid technique for dynamics of rail transit stations classification: a case study by Ahad Amini Pishro, Shiquan Zhang, Alain L’Hostis, Yuetong Liu, Qixiao Hu, Farzad Hejazi, Maryam Shahpasand, Ali Rahman, Abdelbacet Oueslati, Zhengrui Zhang

“…A comprehensive case study on the Chengdu rail transit network validates the model’s efficacy, highlighting its value in optimizing TOD strategies and guiding decision-making processes for urban planners and policymakers. …”
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Adaptive Quantum-Inspired Evolution for Denoising PCG Signals in Unseen Noise Conditions by Lubna Siddiqui, Ashish Mani, Jaspal Singh

“…The filter coefficients were optimised using the proposed QiEA with Adaptive Rotation Gate Operator (ARGO). The proposed algorithm accelerates convergence towards optimal solutions based on fitness feedback, improving filter optimisation while clamping rotation angles to maintain algorithm stability. …”
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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

“…This paper proposes a Distributed Moving Horizon Estimation (DMHE) technique that integrates consensus theory and Moving Horizon Estimation to optimize computational efficiency, minimize communication requirements, and enhance system robustness. …”
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A Metaheuristic Approach Based Feasibility Assessment and Design of Solar, Wind, and Grid Powered Charging of Electric Vehicles by Fayez Alanazi, Mohd Bilal, Ammar Armghan, Md Reyaz Hussan

“…We assess the efficacy of other algorithms in scaling system components by contrasting the performance of the GPCA with those of the Artificial Hummingbird Algorithm (AHA), Flower Pollination Algorithm (FPA), and Whale Optimization Algorithm (WOA). …”
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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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Beyond the Grid: GLRT-Based TomoSAR Fast Detection for Retrieving Height and Thermal Dilation by Nabil Haddad, Karima Hadj-Rabah, Alessandra Budillon, Gilda Schirinzi

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Comparative Assessment of Modulation Strategies in Modular Multilevel Converters: An Attempt for a Better Compromise Between the Efficiency and Capacitor Voltages&#x0027; Dispersio... by Anthony Abdayem, Jean Sawma, Adrian Beneit, Ramon Blasco-Gimenez, Flavia Khatounian, Eric Monmasson

“…The results show that the proposed modulation techniques utilizing the suggested sorting algorithm, effectively decrease the switching number while maintaining the THD of the load currents. …”
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Faults Detection and Diagnosis of a Large-Scale PV System by Analyzing Power Losses and Electric Indicators Computed Using Random Forest and KNN-Based Prediction Models by Yasmine Gaaloul, Olfa Bel Hadj Brahim Kechiche, Houcine Oudira, Aissa Chouder, Mahmoud Hamouda, Santiago Silvestre, Sofiane Kichou

“…Accurate and reliable fault detection in photovoltaic (PV) systems is essential for optimizing their performance and durability. This paper introduces a novel approach for fault detection and diagnosis in large-scale PV systems, utilizing power loss analysis and predictive models based on Random Forest (RF) and K-Nearest Neighbors (KNN) algorithms. …”
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Supervised autoencoder MLP for financial time series forecasting by Bartosz Bieganowski, Robert Ślepaczuk

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A Practical Performance Benchmark of Post-Quantum Cryptography Across Heterogeneous Computing Environments by Maryam Abbasi, Filipe Cardoso, Paulo Váz, José Silva, Pedro Martins

“…National Institute of Standards and Technology (NIST) and global security stakeholders. While theoretical security analysis of these quantum-resistant algorithms has advanced considerably, comprehensive real-world performance benchmarks spanning diverse computing environments—from high-performance cloud infrastructure to severely resource-constrained IoT devices—remain insufficient for informed deployment planning. …”
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Black-box and white-box machine learning tools to estimate the frost formation condition during cryogenic CO2 capture from natural gas blends by Farag M.A. Altalbawy, Fadhel F. Sead, Dharmesh Sur, Anupam Yadav, José Gerardo León Chimbolema, Suhas Ballal, Abhayveer Singh, Anita Devi, Kamal Kant Joshi, Nizomiddin Juraev, Hossein Mahabadi Asl

“…Precise estimation of the CO2 frost formation temperature (FFT) is vital for optimizing CCC processes and maximizing efficiency. …”
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Machine Learning in the National Economy by Azamjon A. Usmonov

“…The practical part of the study included the development of machine learning algorithms for predicting economic indexes. A linear regression model was used to forecast GDP growth, while more complex models, such as random forests and gradient boosting, were applied to analyze more intricate economic relationships. …”
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An uncertain sustainable supply chain network design for regulating greenhouse gas emission and supply chain cost by Amit Kumar, Kaushal Kumar

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A novel sequential block path planning method for 3D unmanned aerial vehicle routing in sustainable supply chains by Muhammad Ikram, Robert Sroufe

“…This study aims to enhance sustainable supply chain management by considering new opportunities for optimizing UAV networks. The primary objective is to develop advanced path planning and routing algorithms that improve the quality of service in a supply chain. …”
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