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2661
Unobtrusive Sleep Posture Detection Using a Smart Bed Mattress with Optimally Distributed Triaxial Accelerometer Array and Parallel Convolutional Spatiotemporal Network
Published 2025-06-01“…For sleep posture classification, we employ an improved density peak clustering algorithm that incorporates the K-nearest neighbor mechanism. …”
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2662
Bearing Fault Diagnosis based on ACSBP Algorithm
Published 2017-01-01“…The diagnostic results show that the ACSBP algorithm has stronger fault tolerance compared with CSBP and PSOBP models,and can effectively improve the accuracy of bearing fault diagnosis.…”
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2663
Efficient hybrid heuristic adopted deep learning framework for diagnosing breast cancer using thermography images
Published 2025-04-01“…Then, the optimal binary thresholding is done to segment the preprocessed images, where optimized the thresholding value using developed Rock Hyraxes Dandelion Algorithm Optimization (RHDAO). …”
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2664
A cellular automata coupled multi-objective optimization framework for blue-green infrastructure spatial allocation
Published 2025-09-01“…In this study, a multi-objective optimization framework was developed to address these challenges by integrating a Cellular Automata (CA)-based hydrological model with the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). …”
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2665
Atomic Energy Optimization: A Novel Meta-Heuristic Inspired by Energy Dynamics and Dissipation
Published 2025-01-01“…AEO models optimization by mimicking the energy accumulation, transfer, and dissipation behaviors observed in atoms, particularly during processes involving electrostatic charge and discharge. …”
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2666
Developing and Implementing an Artificial Intelligence (AI)-Driven System For Electricity Theft Detection
Published 2024-09-01“…Methodology used are data collection, data analysis, feature selection with Chi-Square, feature transformation with Principal Component Analysis (PCA), Support Vector Machine (SVM) and model for electricity theft detection. To achieve this, a Particle Swarm Optimization Algorithm (PSO) was applied to improve training performance of the SVM, using data of meter recharge information collected from Enugu Electricity Distribution Company (EEDC). …”
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2667
Precise Assimilation Prediction of Short-Term and Long-Term Maize Irrigation Water Based on EnKF-DSSAT and Fuzzy Optimization-DSSAT Models
Published 2025-01-01“…We also introduce a Boltzmann machine-based fusion algorithm to improve the model convergence speed and prediction accuracy. …”
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2668
Bacterial Colony Optimization
Published 2012-01-01“…Two types of interactive communication schemas: individuals exchange schema and group exchange schema are designed to improve the optimization efficiency. In the simulation studies, a set of 12 benchmark functions belonging to three classes (unimodal, multimodal, and rotated problems) are performed, and the performances of the proposed algorithms are compared with five recent evolutionary algorithms to demonstrate the superiority of BCO.…”
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2669
Integrating Multilayer Perceptron and Support Vector Regression for Enhanced State of Health Estimation in Lithium-Ion Batteries
Published 2025-01-01“…In order to improve the accuracy of our predictions, we combined these models into a stacked ensemble using a Random Forest (RF) meta-model. …”
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2670
A novel prediction of the PV system output current based on integration of optimized hyperparameters of multi-layer neural networks and polynomial regression models
Published 2025-07-01“…The proposed IMGOMFFNN model is ultimately combined with Polynomial regression model to improve the predictability of the PV system. …”
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2671
A novel Probabilistic Bi-Level Teaching–Learning-Based Optimization (P-BTLBO) algorithm for hybrid feature extraction and multi-class brain tumor classification using ResNet-50 and...
Published 2025-07-01“…The P-BTLBO method combines probabilistic modeling with a bi-level optimization framework to make feature selection better. …”
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2672
Enhancing agricultural sustainability: Optimizing crop planting structures and spatial layouts within the water-land-energy-economy-environment-food nexus
Published 2025-06-01“…In this framework, the NSGA-II algorithm was used to construct the multi-objective optimization model of crop planting structures with consideration of water and energy consumption, greenhouse gas (GHG) emissions, economic benefits, as well as food, land, and water security constraints, while the model for planting spatial layout optimization was established with consideration of crop suitability using the MaxEnt model and the improved Hungarian algorithm. …”
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2673
Improving the efficiency of adsorption filters with a short diffuser by improving their flow part
Published 2024-12-01“…The numerical studies cover various options for backfilling the adsorbent, including layer profiling and the use of adsorbent with different porosity, which allows us to assess the impact of these factors on the aerodynamic resistance and overall efficiency of the filter. A design algorithm is also proposed that ensures optimal compliance between the adsorbent layer thickness and the local flow velocity, which helps to increase the protective action time of the filter and improve the quality of cleaning.…”
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2674
Research on Calibration Method of Laser Camera Sensor
Published 2020-01-01“…In this paper, a laser camera sensor calibration mathematical model was established, and the process of solving the calibration model parameters by the nonlinear least square method and Gauss-Newton iterative method was analyzed, and a L-M algorithm based on maximum likelihood estimation was proposed. …”
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2675
Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments
Published 2025-03-01“…The results show that (i) the lowest <i>t</i> value (0°) captured the microtopograhy of the troughs, while the larger <i>L</i> values paired with a DEM resolution of 50 cm diminished the impact of minor noise, improving the accuracy of trough detection; (ii) the optimized Geomorphon model produced trough maps with a high accuracy, achieving mIOU and F1 Scores of 0.89 and 0.90 in PB and 0.84 and 0.87 in WDL, respectively; and (iii) compared with the polygonal boundaries, the trough maps can derive the heterogeneous features to quantify the degradation of PPG. …”
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2676
Fault classification of meta-action unit using CEEMDAN double-layer decomposition and COA-SVM
Published 2025-12-01“…Third, the model is optimized by the Coati Optimization Algorithm (COA) to optimize the fault classification performance of the SVM to achieve efficient and accurate fault diagnosis of the meta-action unit of the model. …”
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2677
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2678
Advanced Queueing and Location-Allocation Strategies for Sustainable Food Supply Chain
Published 2024-09-01“…<i>Methods:</i> The grasshopper optimization algorithm (GOA), a meta-heuristic algorithm inspired by the behavior of grasshopper swarms, is utilized to solve the model on a large scale. …”
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2679
Shared energy storage planning based on the adjustable potential of data center based on visual IOT platform
Published 2025-08-01“…Based the two-stage stochastic optimization model, a improved L-shaped algorithm is proposed to solve the planning model effectively, reducing computational complexity through problem decomposition. …”
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2680
Medium- and Long-term Runoff Prediction Based on SMA-LSSVM
Published 2022-01-01“…Medium-and long-term runoff prediction is extremely important for flood control,disaster reduction and the utilization efficiency improvement of water resources.To avoid the influence of prediction model parameters on prediction accuracy,this paper proposes a medium-and long-term runoff prediction model based on least squares support vector machine (LSSVM) optimized by the slime mold algorithm (SMA).Firstly,five standard test functions are selected to compare the simulation results of SMA and particle swarm optimization (PSO) algorithms in different dimensions.Secondly,SMA is used to optimize the penalty parameters and kernel parameters of LSSVM,and the comparison models of LSSVM and PSO-LSSVM are constructed.Finally,the models are verified with the monthly runoff of Manwan Hydropower Station Reservoir and Yingluoxia Hydrological Station as prediction examples.The results show that the mean square error of the SMA-LSSVM model is 29.26% and 7.42% lower than those of the LSSVM and PSO-LSSVM models,respectively,in the monthly runoff prediction of the Manwan station,and 32.61% and 6.61% lower,respectively,in the monthly runoff prediction of the Yingluoxia station.The proposed SMA-LSSVM model has better comprehensive prediction performance and also provides a new method for medium- and long-term runoff prediction.…”
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