Task-dependent Optimal Weight Combinations for Static Embeddings by Nathaniel Robinson, Nathaniel Carlson, David Mortensen, Elizabeth Vargas, Thomas Fackrell, Nancy Fulda

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Forest canopy closure estimation in mountainous southwest China using multi-source remote sensing data by Wenwu Zhou, Wenwu Zhou, Qingtai Shu, Cuifen Xia, Li Xu, Qin Xiang, Lianjin Fu, Zhengdao Yang, Shuwei Wang

“…Combined with 54 measured plot data, the improved machine learning model of the Bayesian optimization (BO) algorithm was used to obtain the FCC in the footprint-scale ATLAS footprint. …”
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Predicting Wear Rate and Friction Coefficient of Li₂Si₂O₅ Dental Ceramic Using Optimized Artificial Neural Networks by Marko Pantić, Saša Jovanović, Aleksandar Djordjevic, Suzana Petrović Savić, Milan Radenković, Živče Šarkoćević

“…This study explores the application of artificial neural networks (ANNs) to predict the tribological behavior of dental ceramic lithium disilicate (IPS e.max Cad). A genetic algorithm (GA) was used to optimize the ANN’s hyperparameters, improving its ability to model complex, nonlinear relationships between input variables, including normal load and velocity and output properties such as wear rate and friction coefficients. …”
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A hybrid BOA-SVR approach for predicting aerobic organic and nitrogen removal in a gas-liquid-solid circulating fluidized bed bioreactor by Shaikh Abdur Razzak, Nahid Sultana, S.M. Zakir Hossain, Muhammad Muhitur Rahman, Yue Yuan, Mohammad Mozahar Hossain, Jesse Zhu

“…The downer of a GLSCFB bioreactor provided experimental data on TKN, NH4-N, NO3-N, and TCOD removal. The hybrid optimal intelligence algorithm (BOA-SVR) has improved model accuracy across multiple domains by combining BOA and SVR. …”
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Implementation of Apriori Algorithm in Identifying Purchase Relationships at Bluder Cokro Pakuwon Mall by Angeline Ivana, Indra Maryati

“…This study aims to identify consumer purchasing patterns at the store to enhance promotional strategies and optimize product placement. The research applies the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, which includes phases such as business understanding, data understanding, data preparation, modeling, evaluation, and deployment. …”
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Adaptive neuro-fuzzy inference systems for improved mastitis classification and diagnosis by Javad Shirani Shamsabadi, Saeid Ansari Mahyari, Mostafa Ghaderi-Zefrehei

“…Abstract For modeling dairy cattle data, fuzzy logic offers the capability to manage uncertainty, enhance accuracy, facilitate informed decision-making, and optimize resource allocation. …”
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Machine learning based crystal collimator alignment optimization by Gianmarco Ricci, Marco D’Andrea, Mario Di Castro, Eloise Matheson, Daniele Mirarchi, Andrea Mostacci, Stefano Redaelli

“…This advancement represents a crucial step toward refining the process of identifying the optimal channeling orientation. The algorithm has been tested for the fist time in operation with Pb ion beams at the record energy of 6.8 Z TeV demonstrating its reliability.…”
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Dynamic Aerial Small Target Detection Algorithm Based on Compound Zoom Scaling by Jiang Yuan, Zhu Gaofeng, Zhu Fenghua, Xiong Gang

“…To address these issues, this paper proposes a novel small-object detection algorithm. Firstly, a more efficient backbone network is introduced, and a composite scaling method is employed to optimize the balance among network depth, width, and image resolution. …”
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PSO Based Optimization of Testing and Maintenance Cost in NPPs by Qiang Chou, Daochuan Ge, Ruoxing Zhang

“…The above problems can be formulated by a constrained multiobjective optimization model, which is widely used in many other engineering problems. …”
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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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Bridging ACO-Based Drone Logistics and Computing Continuum for Enhanced Smart City Applications by Salvatore Rosario Bassolillo, Egidio D’Amato, Immacolata Notaro, Luca D’Agati, Giovanni Merlino, Giuseppe Tricomi

“…This paper proposes a comprehensive approach to optimizing urban delivery logistics through a cloud-based model that employs Ant Colony Optimization (ACO) for planning and Model Predictive Control (MPC) for trajectory tracking within a broader Computing Continuum framework. …”
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Algorithms for Load Balancing in Next-Generation Mobile Networks: A Systematic Literature Review by Juan Ochoa-Aldeán, Carlos Silva-Cárdenas, Renato Torres, Jorge Ivan Gonzalez, Sergio Fortes

“…The need for enhanced radio resource allocation schemes, improved user mobility and increased throughput, driven by a rising demand for data, has necessitated the development of diverse algorithms that optimize output values based on varied input parameters. …”
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Validation and Optimization of Suspension Design for Testing Platform Vehicle by Luhang Li, Lin Xu, Hao Cui, Mohamed A. A. Abdelkareem, Zihao Liu, Jingyu Chen

“…The nondominated sorting genetic algorithm (NSGA-II) is used to optimize the damping, stiffness, and installation position of the suspension system. …”
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A comparative study of hybrid adaptive neuro-fuzzy inference systems to predict the unconfined compressive strength of rocks by Wei Cao

“…Hybrid models included support vector regression (SVR) combined with the Seahorse Optimizer (SVSH) and SVR combined with the COOT optimization algorithm (SVCO). …”
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Machine learning-based optimization of photogrammetric JRC accuracy by Qinzheng Yang, Ang Li, Yipeng Liu, Hongtian Wang, Zhendong Leng, Fei Deng

“…Using seven machine learning algorithms, optimization models for photogrammetric JRC accuracy were developed, with Linear Multidimensional Regression and Gaussian Process Regression models improving JRC accuracy by an average of 85.73%. …”
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Statistical Analysis Method for Optimal Prameters of Telemetry Communication by XIE Jun, WU Sailong, HAO Hang, ZHANG Songwei, WU Ruiqing, SUN Xiangyang

“…The results confirm that the method significantly reduces the bit error rate by 3.3% and improves the success rate of deframing in most experimental wells. …”
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Optimization of PID Controllers Using Groupers and Moray Eels Optimization with Dual-Stream Multi-Dependency Graph Neural Networks for Enhanced Dynamic Performance by Vaishali H. Kamble, Manisha Dale, R. B. Dhumale, Aziz Nanthaamornphong

“…This study presents a novel control strategy that integrates the Groupers and Moray Eels Optimization (GMEO) algorithm with a Dual-Stream Multi-Dependency Graph Neural Network (DMGNN) to optimize PID controller parameters. …”
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Adaptive Hybrid PSO-Embedded GA for neuroevolutionary training of multilayer perceptron controllers in VSC-based islanded microgrids by Yared Bekele Beyene, Getachew Biru Worku, Lina Bertling Tjernberg

“…The algorithm’s performance is evaluated against conventional optimization methods, demonstrating significant improvements in accuracy, convergence speed, and consistency across multiple runs. …”
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Enhancing Radial Distribution System Performance Through Optimal Allocation and Sizing of Photovoltaic and Wind Turbine Distribution Generation Units with Rüppell’s Fox Optimizer... by Yacine Bouali, Basem Alamri

“…A novel metaheuristic algorithm, referred to as Rüppell’s fox optimizer (RFO), is proposed to address this optimization problem under various scenarios. …”
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Dynamic Emergency Vehicle Path Planning and Traffic Evacuation Based on Salp Swarm Algorithm by X. H. Duan, J. X. Wu, Y. L. Xiong

“…In view of the rescue delay due to traffic congestion in the urban road network, this paper implemented real-time traffic control with congestion index constraints in emergency vehicle dispatching and proposed a two-stage optimization model and algorithm. In the first stage, salp swarm algorithm (SSA) was combined with Dijkstra algorithm, and a novel hybrid algorithm with new updating rules was designed to get the multiple alternative paths. …”
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