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Investigating the performance of random oversampling and genetic algorithm integration in meteorological drought forecasting with machine learning
Published 2025-05-01“…Therefore, this study aims to evaluate the effectiveness of machine learning methods for meteorological drought estimation and to integrate Random Oversampling (ROS) and Genetic Algorithm (GA) methods to improve estimation accuracy. …”
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1263
OPTIMIZATION OF FUZZY INVENTORY MANAGEMENT IN INDUSTRIAL PROCESSES USING DEEP LEARNING ALGORITHMS: A HYBRID APPROACH FOR ENHANCING DEMAND FORECASTING AND SUPPLY CHAIN EFFICIENCY
Published 2024-12-01“…A mathematical model and algorithmic implementation demonstrate the approach’s effectiveness and a numerical example highlights improvements in inventory control, including reduced holding costs. …”
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1264
Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy
Published 2025-07-01“…Convolutional Neural Networks are used to extract spatial features from agricultural data, while Long Short-Term Memory networks processed time series data. To enhance model performance, the slime mould algorithm is employed for parameter optimization. …”
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1265
Forecasting the daily evaporation by coupling the ensemble deep learning models with meta-heuristic algorithms and data pre-processing in dryland
Published 2025-08-01“…To overcome the drawback that directly using measured evaporation time series to predict evaporation may lead to large error, the Variational mode decomposition (VMD) was used to extract multiscale traits of evaporation time series, and Whale optimization algorithm (WOA) was adopted to find the optimal parameters of VMD, and a novel hybrid deep learning model WOA-VMD-CNN-SSA-BiLSTM was proposed to estimate the evaporation in the Linze County, China. …”
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1266
Multiobjective Optimization of Irreversible Thermal Engine Using Mutable Smart Bee Algorithm
Published 2012-01-01“…The results have been checked with some of the most common optimizing algorithms like Karaboga’s original artificial bee colony, bees algorithm (BA), improved particle swarm optimization (IPSO), Lukasik firefly algorithm (LFFA), and self-adaptive penalty function genetic algorithm (SAPF-GA). …”
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1267
Research review on improving the efficiency of multimodal transportation based on technological solutions
Published 2020-09-01“…Based on the theory of controlled networks and integer linear programming methods, the experts developed mathematical models for the distribution of cargo flows, the choice of the most favorable transportation routes, ideal loading of rolling stock, and transportation of goods using the best forwarding algorithm. …”
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1268
Commercial Vehicle Ride Comfort Optimization Based on Intelligent Algorithms and Nonlinear Damping
Published 2019-01-01“…To improve the reliability of ride comfort optimization and analysis, a ride comfort optimization method based on nonlinear damping and intelligent algorithms is proposed. …”
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1269
Robust Photovoltaic Power Forecasting Model Under Complex Meteorological Conditions
Published 2025-05-01“…To effectively mitigate these limitations, this work proposes a dual-stage feature extraction method based on Variational Mode Decomposition (VMD) and Principal Component Analysis (PCA), enhancing multi-scale modeling and noise reduction capabilities. Additionally, the Whale Optimization Algorithm is adopted to efficiently optimize the hyperparameters of iTransformer for the framework, improving parameter adaptability and convergence efficiency. …”
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1270
Algorithm on joint optimization of power allocation and slot allocation in satellite communication systems
Published 2014-10-01“…An algorithm to jointly optimize the power allocation and the slot allocation in order to improve the utilization efficiency of the limited resources on the satellite was proposed.The basic principles of the mutual compensation and mutual independence between these two resources are explored to pave the way for joint optimization.Considering the differences about each station’s channel condition and capacity requirement,a state-combination model for optimally allocating the resources is setted up,so as to adapt the multi-resource usage pattern with each earth station.Targeting at the energy efficiency,an iterative dual optimization algorithm is proposed,and the final optimal policy for resource allocation with low complexity is obtained.With the simulation and analysis,the proposed joint optimization is verified to perform better than the non-joint ones in the perspective of the energy efficiency,especially when the frequency resource (the carrier number) is less.…”
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1271
Optimization of the Naive Bayes Algorithm with SMOTETomek Combination for Imbalance Class Fraud Detection
Published 2024-11-01Get full text
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1272
Optimization of Communication Quality for Energy-Limited Inspection AAV: A Hybrid Algorithm
Published 2024-01-01“…Numerical results show that the proposed algorithm is effective in optimizing the communication quality of the inspection AAV with limited energy, and its performance is improved by about 15%-50% compared with other benchmarks.…”
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1273
Optimizing Bi-LSTM networks for improved lung cancer detection accuracy.
Published 2025-01-01“…We employed traditional hand-crafted features, such as Gray Level Co-occurrence Matrix (GLCM) features, in conjunction with traditional machine learning algorithms. To explore the potential of deep learning, we also optimized and implemented a Bidirectional Long Short-Term Memory (Bi-LSTM) network for lung cancer detection. …”
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1274
Comprehensive Comparison and Validation of Forest Disturbance Monitoring Algorithms Based on Landsat Time Series in China
Published 2025-02-01“…When considering different forest disturbance types, COLD achieved the highest accuracies for Fire, Harvest, and Other disturbances, while CCDC was most accurate for Forestation. These findings highlight the necessity of region-specific calibration and parameter optimization tailored to specific disturbance types to improve forest disturbance monitoring accuracy, and also provide a solid foundation for future studies on algorithm modifications and ensembles.…”
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Intelligent analysis algorithm for power engineering data based on improved BiLSTM
Published 2025-05-01“…In equipment fault diagnosis, the accuracy of improved BiLSTM under current, voltage, temperature and pressure is significantly higher than that of models such as GRU.…”
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1276
Multi-Level Particle System Modeling Algorithm with WRF
Published 2025-05-01“…To improve modeling efficiency, cascade Bezier curves are designed at different line-of-sights (LoSs), utilizing the weight information of boundary particles to optimize cloud contours. …”
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1277
Detecting Planting Holes Using Improved YOLO-PH Algorithm with UAV Images
Published 2025-07-01“…Lastly, our proposed Siblings Detection Head reduces computational burden while significantly improving detection performance. Ablation experiments demonstrate that compared to baseline models, YOLO-PH exhibits notable improvements of 1.3% in mAP50 and 1.1% in mAP50:95 while simultaneously achieving a reduction of 48.8% in FLOPs and an impressive increase of 26.8 FPS (frames per second) in detection speed. …”
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A Novel Optimization Algorithm for Modifying the Parameter Unit of Solar PV Cell
Published 2022-01-01“…As a result, combining these two mechanisms can considerably improve the whale optimization algorithm capacity to find the optimal answer. …”
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A navigation satellite selection algorithm for optimized positioning based on Gibbs sampler
Published 2020-06-01“…In addition, the scheme is updated by the conditional probability distribution model of the Gibbs sampler algorithm, and it gradually approaches the global optimal solution of the satellite combination with better geometric distribution of the space satellite. …”
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Research on Wellbore Trajectory Optimization and Drilling Control Based on the TD3 Algorithm
Published 2025-06-01“…After reinforcement learning training, the trajectory offset is significantly reduced, and the accuracy is greatly improved. This research shows that the TD3 algorithm is superior to the multi-objective optimization algorithm in optimizing key parameters, such as well deviation, kickoff point (KOP), and trajectory length, especially in well deviation and KOP optimization. …”
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