Modeling and Optimization of Beam Pumping System Based on Intelligent Computing for Energy Saving by Xiaohua Gu, Taifu Li, Zhiqiang Liao, Liping Yang, Ling Nie

“…It firstly employs the general regression neural network (GRNN) algorithm to obtain the best model of the beam pumping system, and secondly searches the optimal operation parameters with improved strength Pareto evolutionary algorithm (SPEA2). …”
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Technique on Vehicle Damage Assessment After Collisions Using Optical Radar Technology and Iterative Closest Point Algorithm by Shih-Lin Lin, Yi-Hsuan Chen

“…The contributions of this study lie in integrating LiDAR technology with advanced point cloud processing algorithms and a deep learning optimization model for vehicle damage assessment, demonstrating high precision and cost-effectiveness. …”
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Genetic Neuro-Fuzzy Approach towards Routing in Industrial IoT by Olena Semenova, Natalia Kryvinska, Andriy Semenov, Volodymyr Martyniuk, Olha Voitsekhovska

“…A rules base was developed. To improve the rule base of the ANFIS, a genetic algorithm was proposed. …”
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Improved Correlation of Oil Recovery Factor for Water Driven Reservoirs in the Niger Delta by Ayodele Daniel, Faisal Olasubomi Olanipekun, Sunday Oloruntoba Isehunwa

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An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization by Warda M. Shaban

“…We feed these extracted features to FSS, which uses a proposed method to select the most important and effective features. The proposed method is called the Dimensional Archimedes Optimization Algorithm (DAOA). …”
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Color Dominance-Based Polynomial Optimization Segmentation for Identifying Tomato Leaves and Fruits by Juan Pablo Guerra Ibarra, Francisco Javier Cuevas de la Rosa, Alicia Linares Ramirez

“…Similarly, a UNetmodel is used for semantic segmentation, the results of which are inferior to those obtained by the proposed interpolation optimization method. The most significant contribution of the interpolation method is that it requires only a single iteration to generate the initial data, in contrast to the iterative search required by the greedy algorithm and the lengthy training process and video card dependency of the UNet model. …”
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Hybrid Model for 6G Network Traffic Prediction and Wireless Resource Optimization by Mohammed Anis Oukebdane, A. F. M. Shahen Shah, Md Baharul Islam, John Ekoru, Milka Madahana

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Towards few-shot learning with triplet metric learning and Kullback-Leibler optimization by Yukun Liu, Xiaojing Wei, Daming Shi, Dan Xiang, Junliu Zhong, Hai Su

“…In training, the deep learning and expectation-maximization algorithm are used to optimize models. Intensive experiments have been conducted on three popular benchmark datasets, and the experimental results show that this method significantly improves the classification ability of few-shot learning tasks and obtains the most advanced performance.…”
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Collision-inducing method for UAV evasive maneuvers based on receding horizon optimization by Haonan Tang, Zhigong Tang, Gong Chen, Jifeng Guo

“…The obstacle potential field-based target selection algorithm was employed to identify the most appropriate target obstacle, while the induced trajectory was determined through a combination of receding horizon optimization and the hp-adaptive pseudo-spectral method. …”
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Multibranch semantic image segmentation model based on edge optimization and category perception. by Zhuolin Yang, Zhen Cao, Jianfang Cao, Zhiqiang Chen, Cunhe Peng

“…Second, a category perception module is used to learn category feature representations and guide the pixel classification process through an attention mechanism to optimize the resulting segmentation accuracy. Finally, an edge optimization module is used to integrate the edge features into the middle and the deep supervision layers of the network through an adaptive algorithm to enhance its ability to express edge features and optimize the edge segmentation effect. …”
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Optimization Path and Design of Intelligent Logistics Management System Based on ROS Robot by Ruijie Wu

“…Therefore, this paper aimed to design an intelligent logistics management system based on ROS robot and proposed to use the A-star algorithm to calculate the shortest path of the robot so as to achieve the optimal path. …”
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Optimized Electric Vehicles Wireless Charging: Applicative Models for Supporting Decision Makers by Cristian Giovanni Colombo, Ryosuke Ota, Michela Longo

“…The work proposes an optimization algorithm for each context and identifies outputs for 3 different car models with different heights above the ground (0.10 m, 0.20 m and 0.30 m). …”
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Integrated Approach to Optimizing Selection and Placement of Water Pipeline Condition Monitoring Technologies by Diego Calderon, Mohammad Najafi

“…This article introduces a unified framework and methods for optimally selecting condition monitoring technologies while locating their deployment at the most vulnerable pipe segments. …”
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Model Optimization for High-Yield Biocrude in Co-Hydrothermal Liquefaction of Municipal Sludge by Botian HAO, Yunfei DIAO, Ya WEI, Donghai XU

“…After training with the Levenberg-Marquardt algorithm, the model′s R2 significantly improved to 0.9989, demonstrating the superiority of neural networks in modeling nonlinear complex systems. …”
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EFFICACY OF OPTIMIZED REMINERALIZING THERAPY IN POST-COVID-19 PATIENTS: EVALUATION OF RESULTS by N.M. Savielieva, M.E. Diasamidze

“…To correct the identified disorders and prevent the occurrence and development of carious lesions, we applied an improved algorithm of prophylaxis of dental enamel diseases using remineralizing therapy. …”
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An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things by Mai Alduailij

“…For the feature selection process, the binary grey wolf optimization (BGWO) model is employed to identify and retain the most significant features in the dataset. …”
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Meta-Features Extracted from Use of kNN Regressor to Improve Sugarcane Crop Yield Prediction by Luiz Antonio Falaguasta Barbosa, Ivan Rizzo Guilherme, Daniel Carlos Guimarães Pedronette, Bruno Tisseyre

“…A comparative analysis is presented with a projection based on the Uniform Manifold Approximation and Projection (UMAP) algorithm, showing that MFs had more proximity than the original features when projected, which demonstrates that MFs revealed a clear formation of well-defined clusters, with most points within each group sharing the same color, suggesting greater uniformity in the predicted values. …”
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Research Progress on Machine Learning Prediction of Compressive Strength of Nano-Modified Concrete by Ruyan Fan, Ankang Tian, Yikun Li, Yue Gu, Zhenhua Wei

“…Nano-modified concrete has attracted wide attention due to its improved mechanical properties. Among them, compressive strength is the most critical indicator. …”
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Low-cost fabrication and comparative evaluation of machine learning algorithms for flexible PDMS-based hexagonal patch antenna by Srivatsan Sarvesan, Mettu Goutham Reddy, S. S. Karthikeyan, Praveen K. Sekhar

“…To accelerate the design process and determine the most effective model for predicting optimal geometrical parameters that yield improved impedance matching at the target frequency, four supervised machine learning algorithms including Random Forest, XGBoost, CatBoost and LightGBM were evaluated and compared. …”
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Artificial Bee Colony Algorithm Based on the Division Between Exploration and Exploitation and Its Application in Esophageal Cancer Prediction by WANG Yingcong, YAN Jun, SUN Junwei, WANG Yanfeng

“…The Wilcoxon test results indicated that there was no significant difference between ABC_DEE and GABC, but ABC_DEE significantly outperformed the other algorithms. When <italic>D</italic>=20, ABC_DEE was superior to the comparison algorithms on at least 47 functions and inferior on at most 26 functions. …”
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