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1561
Comparative analysis of machine learning models for malaria detection using validated synthetic data: a cost-sensitive approach with clinical domain knowledge integration
Published 2025-07-01“…XGBoost achieved optimal performance with highest $$\text {AUC}$$ (0.956, 95% $$\text {CI}$$ : 0.952–0.961) and competitive clinical cost (5,496), representing 2.8% improvement over Random Forest. …”
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1562
APG mergence and topological potential optimization based heuristic user association strategy
Published 2022-06-01“…Methods:The network scalable degree was designed as a measure of scalability,and then a user association strategy to improve network scalable degree was studied by using optimization theory. 1) For modelling the optimization problem, firstly, the network coupling degree, representing the degree of association among nodes, was constructed to establish the mathematical relationship between the network scalable degree and AP group (APG).Thus,the problem of improving the network scalable degree was modeled as the problem of minimizing the network coupling degree.Then,a multi-objective optimization problem of minimum network coupling degree and maximum user rate was established to find the balance between network scalable degree and network service quality. 2) For solving the optimization problem,to avoid the high computational complexity,a heuristic user association strategy based on APG mergence and topological potential optimization was proposed.With the proposed algorithm,the number of APG could be reduced by APG mergence,and the number of APG that AP belongs to could be reduced by AP exiting APG. …”
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1563
An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things
Published 2025-08-01“…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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1564
Reliability evaluation of dynamic face recognition systems based on improved Fuzzy Dynamic Bayesian Network
Published 2020-03-01“…In this article, we propose a novel evaluation method with True Positive Identification Rate in dynamic and M:N mode and create a novel evaluation model of system reliability with the improved Fuzzy Dynamic Bayesian Network. Subsequently, we infer to solve the fuzzy reliability state probabilities of the six systems with Netica and get two most important factors with the improved fuzzy C-means algorithm. …”
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1565
Optimizing Fairness and Spectral Efficiency With Shapley-Based User Prioritization in Semantic Communication
Published 2025-01-01“…The Shapley-based approach outperforms established methods, including the Hungarian algorithm, reinforcement learning algorithms like Deep Q-Network (DQN) and Proximal Policy Optimization (PPO), as well as conventional 4G and 5G resource allocation strategies. …”
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1566
Numerical Investigation and Optimization of Transpiration Cooling Plate Structures with Combined Particle Diameter
Published 2025-06-01“…Further optimization with the multi-objective genetic algorithm (MOGA) determines the optimal structural parameters. …”
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1567
Machine-Learning-Algorithm-Assisted Portable Miniaturized NIR Spectrometer for Rapid Evaluation of Wheat Flour Processing Applicability
Published 2025-05-01“…By employing an improved whale optimization algorithm (iWOA) coupled with a successive projections algorithm (SPA), we selected the 20 most informative wavelengths (MIWs) from the full range spectra, allowing the iWOA/SPA-SOA-SVR model to predict SV with correlation coefficient and root-mean-square errors in prediction (R<sub>P</sub> and RMSE<sub>P</sub>) of 0.9605 and 0.2681 mL. …”
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1568
EFFICACY OF OPTIMIZED REMINERALIZING THERAPY IN POST-COVID-19 PATIENTS: EVALUATION OF RESULTS
Published 2024-06-01“…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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1569
Comprehensive Performance-Oriented Multi-Objective Optimization of Hemispherical Resonator Structural Parameters
Published 2025-02-01“…Subsequently, the NSGA-II algorithm is applied to perform multi-objective mapping of these parameters, achieving an optimized resonator with a 4.61% increase in the minimum frequency difference from interference modes and a substantial improvement in thermoelastic damping of approximately 70.41%. …”
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1570
An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization
Published 2025-05-01“…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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1571
Applications of Recent Metaheuristic Algorithms for Loss Reduction in Distribution Power Systems considering Maximum Penetration of Photovoltaic Units
Published 2023-01-01“…Photovoltaic units (PVUs) are placed optimally by implementing the Coot optimization algorithm (COOA), the archimedes optimization algorithm (AOA), the transient search optimization algorithm (TSOA), the crystal structure algorithm (CrSA), the war strategy optimization algorithm (WSA), and the average and subtraction-based optimizer (ASBO). …”
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1572
Location Optimization Model of a Greenhouse Sensor Based on Multisource Data Fusion
Published 2022-01-01“…In this paper, a model based on the moving least square method in the fusion algorithm is proposed to study the optimal monitoring point of the sensor in the greenhouse and determine the most suitable installation position of the sensor in the greenhouse to improve the control effect of the temperature control device of the system. …”
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1573
Color Dominance-Based Polynomial Optimization Segmentation for Identifying Tomato Leaves and Fruits
Published 2024-10-01“…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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1574
Research on Optimization of Large-Scale Heterogeneous Combat Network Based on Graph Embedding
Published 2025-01-01“…It has shown a 17.23% improvement in this aspect compared to HCNOF0 and a 6.89% enhancement when compared to the GE-SU-EANet algorithm, underscoring its advantages in both optimization performance and cost reduction. …”
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1575
Contextual Regularization-Based Energy Optimization for Segmenting Breast Tumor in DCE-MRI
Published 2025-01-01“…An iterative gradient descent algorithm is engaged to minimize the energy-based cost function, obtaining stable convergence towards the optimal solution. …”
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SIMULATION AND OPTIMIZATION AS A TOOL FOR THE DEVELOPMENT OF HIGH EFFECTIVE TECHNOLOGICAL SCHEMES OF DISTILLATION
Published 2017-06-01“…The data are presented for the optimization algorithms of the PTCDS. A comparison is made of conventional and developed distillation schemes using the energy consumption criterion. …”
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1578
Towards few-shot learning with triplet metric learning and Kullback-Leibler optimization
Published 2025-06-01“…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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1579
Predicting compressive strength of concrete at elevated temperatures and optimizing its mixture proportions
Published 2025-07-01“…The Cuckoo search algorithm was then employed to optimize mix designs, balancing high-temperature strength, cost and sustainability. …”
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1580
Optimizing the lifetime of wireless sensor networks via reinforcement-learning-based routing
Published 2019-02-01“…Reinforcement-learning-based routing protocol takes advantage of the intelligent algorithm of reinforcement learning to search for the optimal routing path for data transmission. …”
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