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1181
Development of weighted residual RNN model with hybrid heuristic algorithm for movement recognition framework in ambient assisted living
Published 2025-02-01“…For achieving a better training and testing process, the weights in the RRNN model are optimally selected by using the hybrid algorithm named Hybrid Rat Swarm with Coati Optimization Algorithm, which is developed with the integration of the Rat Warm Optimization and Coati Optimization. …”
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1182
Optimal load frequency control system for two-area connected via AC/DC link using cuckoo search algorithm
Published 2025-06-01“…Results: The CSA was compared with particle swarm optimization algorithm (PSO) under identical conditions. …”
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1183
Improving Forest Above-Ground Biomass Estimation Accuracy Using Multi-Source Remote Sensing and Optimized Least Absolute Shrinkage and Selection Operator Variable Selection Method
Published 2024-11-01“…Compared to the optimal SGBoost model with the Lasso variable selection method (R<sup>2</sup> of 0.69, RMSE of 18.63 Mg/ha), the VIF-Lasso method improves R<sup>2</sup> by 0.06 and reduces RMSE by 2.15 Mg/ha, while the Lasso-GA method improves R<sup>2</sup> by 0.04 and reduces RMSE by 1.93 Mg/ha. …”
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1184
The prediction of karst-collapse susceptibility levels based on the ISSA-ELM integrated model
Published 2025-05-01“…To address the limitations of conventional prediction methods, in this study, we introduce an enhanced predictive model, the improved sparrow search algorithm-optimized extreme learning machine (ISSA-ELM), for accurate karst-collapse susceptibility assessment. …”
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1185
Using artificial intelligence methods for the optimal synthesis of reversible networks
Published 2024-11-01“…The ant colony optimization algorithms were improved, including several changes to the proposed data representation model, structure, and operational principles of the synthesis algorithm, enabling effective synthesis of devices on the NCT basis along with Fredkin gates. …”
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1186
An Improved UNet-Based Path Recognition Method in Low-Light Environments
Published 2024-11-01“…The optimal attention mechanism is incorporated into the optimized network to enhance the model’s ability to detect path edges and improve detection performance. …”
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1187
Do Sharpness-Based Optimizers Improve Generalization in Medical Image Analysis?
Published 2025-01-01“…These sharpness-based optimizers have shown improvements in model generalization compared to conventional stochastic gradient descent optimizers and their variants on general domain image datasets, but they have not been thoroughly evaluated on medical images. …”
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1188
PSO-FDM (Particle Swarm Optimization-Finite Difference Method)-Based Simulation Model of Temperature and Velocity of Full-Scale Continuous Annealing Furnace
Published 2024-10-01“…To improve the prediction accuracy for different strip sizes, the PSO optimization algorithm was employed to determine the optimal heat transfer coefficient for each strip size. …”
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1189
Research on the Gas Emission Quantity Prediction Model of Improved Artificial Bee Colony Algorithm and Weighted Least Squares Support Vector Machine (IABC-WLSSVM)
Published 2022-01-01“…In order to further accurately predict gas emission of working face, this paper proposes a prediction model of gas emission of working face based on the combination of improved artificial bee colony algorithm and weighted least squares support vector machine (IABC-WLSSAVM). …”
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1190
KMOBPSO-Based High Reliability Controller Placement Algorithm in SDN
Published 2015-06-01“…N+1 redundancy backup model was applied to controller placement problem in SDN in order to solve single node failure problem and to improve system reliability with taking system cost and latency into consideration,and the problem was abstracted as a multi-objective optimization problem. …”
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1191
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1192
An Improved DGA Feature Clustering-Based Method for Transformer Fault Diagnosis
Published 2025-01-01“…This paper also uses genetic algorithm (GA) to optimize multiple data clustering spaces and improve clustering effect. …”
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1193
Sustainable Mineral Processing Technologies Using Hybrid Intelligent Algorithms
Published 2025-06-01“…The proposed control algorithm reduces chromium losses in tailings from 7.5% to 5.5%, while improving concentrate quality by 3–6%. …”
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1194
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1195
Multi-Parameter Optimization of Angle Transmission Ratio of Steer-by-Wire Vehicle
Published 2025-06-01“…The new control strategy uses a genetic algorithm to optimize the yaw rate and lateral acceleration gain values at different speeds, and the two are weighted. …”
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1196
A dual-phase deep learning framework for advanced phishing detection using the novel OptSHQCNN approach
Published 2025-07-01“…The final phase involves classifying the data using the Shallow hybrid quantum-classical convolutional neural network (SHQCNN) model. To improve the effectiveness of the classification approach, the hyperparameters present in the SHQCNN model are fine-tuned using the shuffled shepherd optimization algorithm (SSOA). …”
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1197
Application Study on CPSO-FLN Model in the Steam Turbine Heat Rate Forecast
Published 2019-08-01“…The cloud model based adaptive weight strategy is introduced into the particle swarm algorithm such that the weight of the particle swarm algorithm can be self-adaptively adjusted to improve the global optimization performance of the PSO algorithm by taking advantage of the randomness and stability of cloud droplets. …”
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1198
An Assist-as-Needed Control Strategy Based on a Subjective Intention Decline Model
Published 2024-11-01“…The subjective intention decline module collects surface electromyography (sEMG) data during patient training and optimizes support vector machine (SVM) using quantum particle swarm optimization (QPSO) algorithms to establish a subjective intention decline model. …”
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1199
Improving lifetime of WSN using modified Moth Flame Optimization
Published 2023-09-01Get full text
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1200
Evolutionary Algorithms for the Optimal Design of Robotic Cells: A Dual Approximation for Space and Time
Published 2025-07-01“…Subsequently, an ant colony optimization algorithm is used to optimize the robots’ trajectories, minimizing cycle time. …”
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