Web Application for Mathematical Modeling of Unsteady Oil Flow in Porous Medium by A. A. Mazitov

“…The analysis and interpretation of hydrodynamic research data are based on theoretical models and computational algorithms. Despite the demand for this topic, numerous issues related to unsteady fluid flows in oil reservoirs still require solutions. …”
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Analysing and Forecasting the Energy Consumption of Healthcare Facilities in the Short and Medium Term. A Case Study by Ali Koç, Serap Ulusam Seçkiner

“…Nevertheless, when considering the computational time for all regression models, the single models have better computational times, although the error metrics are not as good as for the ensemble models. …”
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Novel method for robust bilateral filtering point cloud denoising by Huan Yang, Wei Wang, Yue Wang, Peng Wang

“…Results indicate that the proposed method yielded the most accurate normals compared to PCA, Jet, and VCM normal estimation algorithms. Moreover, when compared to algebraic point set surfaces (APSS), robust implicit moving least squares (RIMLS), anisotropic weighted locally optimal projection (AWLOP), bilateral filtering, and guided filtering point cloud denoising algorithms, the proposed method consistently achieved the smallest MSE and the highest SNR in most cases on the dataset used in this study.…”
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Intelligent monitoring and control of farmland based on edge-cloud collaboration and digital twin for digital energy management: investment benefit analysis by Zheng Liu

“…In terms of intelligent control, deep reinforcement learning is used to optimize irrigation decision-making, and adaptive algorithms are combined to improve the flexibility of agricultural equipment scheduling. …”
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Adaptive Path Planning for Multi-Drone Systems Based on SFS, DPF, and Learning Based Refinement by Srwa Ahmed Mustafa, Amin Salih Kakshar

“…The existing algorithms, such as A*, Dijkstra’s, RRT, and ACO, fail to deliver satisfactory results while generating significant computational costs during real-time power consumption and dynamics avoidance attempts. …”
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ADeepWeeD: An adaptive deep learning framework for weed species classification by Md Geaur Rahman, Md Anisur Rahman, Mohammad Zavid Parvez, Md Anwarul Kaium Patwary, Tofael Ahamed, David A. Fleming-Muñoz, Saad Aloteibi, Mohammad Ali Moni, PhD

“…Efficient weed management in agricultural fields is essential for attaining optimal crop yields and safeguarding global food security. …”
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Augmenting Naïve Bayes Classifiers with <i>k</i>-Tree Topology by Fereshteh R. Dastjerdi, Liming Cai

“…As powerful tools for classification tasks, Bayesian classifiers often require computing joint probability distributions, which can be computationally intractable due to potential full dependencies among feature variables. …”
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Efficient Resources Provisioning Based on Load Forecasting in Cloud by Rongdong Hu, Jingfei Jiang, Guangming Liu, Lixin Wang

“…We propose a multi-step-ahead load forecasting method, KSwSVR, based on statistical learning theory which is suitable for the complex and dynamic characteristics of the cloud computing environment. It integrates an improved support vector regression algorithm and Kalman smoother. …”
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The Sea-Based Waste Collection Routing Problem Using a Novel Value Recovery Function by Ricardo C. Alindayu II, Jayne Lois San Juan, Charlle L. Sy

“…A modified ant colony optimization algorithm was constructed to arrive at near-optimal solutions within a reasonable computing time given the problem’s NP-hard nature. …”
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Analysis of Energy Consumption in a Federated Learning-Based Zero-Touch Network by Urooj Yousuf Khan, Musharaf Ali Talpur, Umme Laila, Samar Raza Talpur

“…A pivotal point in Zero-Touch Networks is the selection of an optimal machine-learning algorithm. One such algorithm is Federated learning which relies on local updates of a global model. …”
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An Integrated Strategy for Interpretable Fault Diagnosis of UAV EHA DC Drive Circuits Under Early Fault and Imbalanced Data Conditions by Yang Li, Zhen Jia, Jie Liu, Kai Wang, Peng Zhao, Xin Liu, Zhenbao Liu

“…This process effectively saves computational resources while significantly reducing the risk of overfitting. …”
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Bayesian adaptation in Poisson cognitive systems by Aleksander A. Solodov

“…In particular, to describe the stochastic properties of cognitive systems and the possibility of creating an optimal algorithm, the Bayesian approach recognized in a number of philosophical works is applied.The optimal estimate by the criterion of the minimum standard error is, as is known, a posteriori mathematical expectation of a random estimated value, which is applied in this work. …”
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Machine learning approaches reveal methylation signatures associated with pediatric acute myeloid leukemia recurrence by Yushuang Dong, HuiPing Liao, Feiming Huang, YuSheng Bao, Wei Guo, Zhen Tan

“…Incremental Feature Selection was performed to evaluate these results, and optimal subsets were identified using Decision Tree and Random Forest methods. …”
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Ensemble learning guided survival prediction and chemotherapy benefit analysis in high-grade chondrosarcoma: A study based on the surveillance, epidemiology, and end results (SEER)... by Xu Zheng, Longqiang Shu, Shanyi Lin, Hanqiang Jin, Xiaoyu Wang, Ting Yuan

“…Ensemble learning has better overall performance than single computational approaches for clinical decision. The primary objective was to select prognostic variables and develop optimal ensemble learning algorithms for survival prediction and analyzing chemotherapy benefit in high-grade chondrosarcoma. …”
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Rail Transit Prediction Based on Multi-View Graph Attention Networks by Li Wang, Xin Wang, Jiao Wang

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A Review on the Advances, Applications, and Future Prospects of Post-Quantum Cryptography in Blockchain and IoT by Yong Wang, Eddie Shahril Ismail

“…This framework combines hybrid key exchange mechanisms, dual-signature schemes, and PQC-compatible Merkle trees, supported by a discrete multi-objective optimization model to select algorithms that meet real-world constraints. …”
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APPLICATION OF ARTIFICIAL NEURON NETWORK AND FUZZY INFERENCE IN THE HOUSEPLANT WATERING INTELLIGENT SYSTEM by Roman Korostenskyi, Igor Olenych

“…Moreover, the proposed algorithms can be implemented on low-power computational platforms commonly used in automation and IoT systems. …”
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Prediction of Thermal and Optical Properties of Oxyfluoride Glasses Based on Interpretable Machine Learning by Yuhao Xie, Xiangfu Wang

“…Based on the components of glasses, four algorithms, namely K-Nearest Neighbor, Random Forest, Support Vector Machine, and eXtreme Gradient Boosting, were used to construct an optimal machine learning model to predict the thermal and optical properties of oxyfluoride glass, namely glass transition temperature, density, Abbe number, liquidus temperature, thermal expansion coefficient, and refractive index. …”
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How low can you go: evaluating electrode reduction methods for EEG-based speech imagery BCIs by Maurice Rekrut, Maurice Rekrut, Johannes Ihl, Tobias Jungbluth, Antonio Krüger, Antonio Krüger

“…In this study, we evaluated several electrode reduction algorithms in combination with various feature extraction and classification methods across three distinct EEG-based speech imagery datasets to identify the optimal number and position of electrodes for SI-BCIs. …”
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Skip-Connected CNN Exploiting BNN Surrogate for Antenna Modelling by Yubo Tian, Jinlong Sun, Zhiwei Zhu

“…The combination of evolutionary algorithms with full-wave electromagnetic (EM) simulation software is an effective method for antenna optimal design. …”
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