Surrogate modeling of passive microwave circuits using recurrent neural networks and domain confinement by Kaustab C. Sahu, Slawomir Koziel, Anna Pietrenko-Dabrowska

“…The network’s hyperparameters are adjusted through Bayesian Optimization (BO). Utilization of frequency as a sequential variable handled by RNN is a distinguishing feature of our approach, which leads to the enhancement of dependability and cost efficiency. …”
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Leveraging petrophysical and geological constraints for AI-driven predictions of total organic carbon (TOC) and hardness in unconventional reservoir prospects by Nandito Davy, Ammar El-Husseiny, Umair bin Waheed, Korhan Ayranci, Manzar Fawad, Mohamed Mahmoud, Nicholas B. Harris

“…Our optimized models achieved R2 (coefficient of determination) of 0.89 and RMSE (root-mean-square error) of 0.47 for TOC predictions and 0.90 and 34.8 for hardness predictions, reducing RMSE by up to 13.52% compared to the unconstrained model. …”
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Frequency Regulation Provided by Doubly Fed Induction Generator Based Variable-Speed Wind Turbines Using Inertial Emulation and Droop Control in Hybrid Wind–Diesel Power Systems by Muhammad Asad, José Ángel Sánchez-Fernández

“…To achieve such goals, we used the above-mentioned proposed controls (EI&P and PC) and optimally tuned them using the Student-Psychology-Based Algorithm (SPBA). …”
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Vibration Control of Wind Turbine Blade Based on Data Fitting and Pole Placement with Minimum-Order Observer by Tingrui Liu, Lin Chang

“…It not only ensures certain accuracy, but also greatly improves the speed of calculation. The Wilson method, developed on the basis of the blade momentum theory, is adopted to optimize the structural parameters of the blade, with all parameters fitted as general model Sin6 (Sum of Sine) fitting curves. …”
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Local Search-Based Metaheuristic Methods for the Solid Waste Collection Problem by Haneen Algethami

“…Local search methods, notably GLS, have significantly improved the route construction process. The nearest neighbour algorithm has often outperformed the Clarke and Wright's methods. …”
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Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

“…Using S-G smoothing filtering (S-G), multivariate scattering correction (MSC), standard normal transformation (SNV), second derivative (SD), reciprocal logarithm (LR) and continuum removal (CR) to preprocess the data, the spectral characteristics and their correlation with water content were analyzed. In order to further improve the prediction ability of the model, the competitive adaptive reweighting method (CARS) was used to optimize the characteristic band, and a prediction model was established by combining random forest regression (RFR), least squares support vector regression (LSSVR) and particle swarm optimization least squares support vector regression (PSO-LSSVR). …”
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Automating attendance management in human resources: A design science approach using computer vision and facial recognition by Bao-Thien Nguyen-Tat, Minh-Quoc Bui, Vuong M. Ngo

“…Haar Cascade is a cost-effective and user-friendly machine learning-based algorithm for detecting objects in images and videos. …”
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Experimental Study on Evaluation of Organization Collaboration in Prefabricated Building Construction by Dingjing Bao, Yuan Chen, Shuai Wan, Jinlai Lian, Ying Lei, Kaizhe Chen

“…Prefabricated buildings have become important in the transformation and upgrading of the construction industry due to their advantages, including high efficiency, energy conservation, low cost, and environmental friendliness. To further promote the wide application of prefabricated construction, the improvement of construction organization design has become an urgent problem to be solved. …”
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Inversion model of stress state reconstruction for geological hazard pipelines based on digital twin by Xue Luning, Tian Mingliang, Zhao Juncheng

“…The mechanical state of the physical pipeline is mapped in real time by the digital twin, the numerical simulation and multi-source monitoring data are integrated, and the parameters of the twin model are dynamically optimized by combining the optimization algorithms of Particle Swarm Optimization (PSO) and Support Vector Machine (SVM), so as to realize the real-time prediction of the pipeline stress state and the dynamic updating of the disaster scenario. …”
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Network-coding-based two-way relay cooperation with energy harvesting by Shunwai Zhang, Rongfang Song, Tao Hong

“…Furthermore, we analyze the outage probability and bit error rate of the system when the optimal antenna selection algorithm is adopted at the relay to transmit data. …”
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Thermal-aware resource allocation in earliest deadline first using fluid scheduling by Muhammad Naeem Shehzad, Qaisar Bashir, Ghufran Ahmad, Adeel Anjum, Muhammad Naeem Awais, Umar Manzoor, Zeeshan Azmat Shaikh, Muhammad A Balubaid, Tanzila Saba

“…Thermal issues in microprocessors have become a major design constraint because of their adverse effects on the reliability, performance and cost of the system. This article proposes an improvement in earliest deadline first, a uni-processor scheduling algorithm, without compromising its optimality in order to reduce the thermal peaks and variations. …”
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Automatic collaborative water surface coverage and cleaning strategy of UAV and USVs by Tianping Deng, Xiaohui Xu, Zeyan Ding, Xiao Xiao, Ming Zhu, Kai Peng

“…The simulation results show that the proposed algorithms have higher generality and flexibility while effectively improving computational efficiency and reducing actual cleaning costs compared with other schemes.…”
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Monitoring of Transformer Hotspot Temperature Using Support Vector Regression Combined with Wireless Mesh Networks by Naming Zhang, Guozhi Zhao, Liangshuai Zou, Shuhong Wang, Shuya Ning

“…Subsequently, this study employed a Support Vector Regression (SVR) algorithm to train the sample dataset, optimizing the SVR model using a grid search and cross-validation to enhance the predictive accuracy. …”
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Robust design of bicycle infrastructure networks by Christoph Steinacker, Mads Paulsen, Malte Schröder, Jeppe Rich

“…In this paper, we approach the problem from two perspectives: direct optimization methods, which generate near-optimal solutions using operations research techniques, and conceptual heuristics, which offer intuitive and scalable algorithms grounded in network science. …”
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Machine Learning-Augmented Triage for Sepsis: Real-Time ICU Mortality Prediction Using SHAP-Explained Meta-Ensemble Models by Hülya Yilmaz Başer, Turan Evran, Mehmet Akif Cifci

“…<b>Background/Objectives:</b> Optimization algorithms are acknowledged to be critical in various fields and dynamical systems since they provide facilitation in identifying and retrieving the most possible solutions concerning complex problems besides improving efficiency, cutting down on costs, and boosting performance. …”
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Dispatching strategy of shared bicycles for morning peak tidal travel based on spatial distribution by Xiangyu Lei, Jiaqi Yang

“…The study identifies the spatial distribution characteristics of the tidal phenomenon by analyzing the riding order and electronic fence data and combining them with the KD-Tree algorithm; subsequently, a demand prediction model based on the XGBoost algorithm and a hierarchical scheduling model based on the greedy algorithm are constructed to dynamically optimize the spatial distribution of the bicycle resources with the demand fluctuation as the guide. …”
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Core-periphery structure for district metered area partitioning in urban water distribution systems by Rair Solis Jacome, Thomaz Anchieta, Bruno M. Brentan, Manuel Herrera, Xitlali Delgado Galvan, Jose Antonio Arciniega Nevarez, Jesus Mora Rodriguez

“…The proposed core-periphery-informed DMA design integrates hydraulic and topological analyses to identify central and peripheral network areas, applies a community structure detection algorithm conditioned by these areas, and uses an optimisation model to determine the optimal placement of boundary devices, enhancing network resilience and reducing costs. …”
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Smart estimation of protective antioxidant enzymes’ activity in savory (Satureja rechingeri L.) under drought stress and soil amendments by Amin Taheri-Garavand, Mojgan Beiranvandi, Abdolreza Ahmadi, Nikolaos Nikoloudakis

“…Specifically, using biochar and superabsorbent led to improved homeostasis under water deficit as reflected by lower MDA levels. …”
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Electric Submersible Pump Fault Diagnosis Based on Laplacian Eigenmaps and Weighted Extreme Learning Machine by XU Zekun, FU Jun, GAO Xiaoyong, ZHANG Yu, LI Qiang, TAN Chaodong

“…In response to the serious imbalance in the data collected by ESP, firstly, a fault diagnosis model is established using a weighted extreme learning machine; Then, to solve the problems of insufficient algorithm learning, high computational costs caused by weighted strategies, and poor performance in applying to high-dimensional feature spaces, the Laplacian eigenmaps method is introduced to further optimize the model; finally, the effectiveness of the proposed method was validated on the TE chemical process dataset, and the practicality of the algorithm was experimentally validated on the real-time fault dataset of electric submersible pump. …”
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Revolutionizing Supply Chain Management With AI: A Path to Efficiency and Sustainability by Kassem Danach, Ali El Dirani, Hassan Rkein

“…Through an in-depth analysis of various AI techniques&#x2014;such as machine learning, predictive analytics, and optimization algorithms&#x2014;this study offers novel insights into their applicability in solving complex supply chain problems like demand forecasting, inventory management, and logistics optimization. …”
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