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Data Decomposition Modeling Based on Improved Dung Beetle Optimization Algorithm for Wind Power Prediction
Published 2024-12-01“…To enhance prediction accuracy, this paper presents a hybrid wind power prediction model that integrates the improved complementary ensemble empirical mode decomposition (ICEEMDAN), the RIME optimization algorithm (RIME), sample entropy (SE), the improved dung beetle optimization (IDBO) algorithm, the bidirectional long short-term memory (BiLSTM) network, and multi-head attention (MHA). …”
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Modeling and Simulation of English Speech Rationality Optimization Recognition Based on Improved Particle Filter Algorithm
Published 2020-01-01“…The system has reasonable recognition ability for general speech, and the improved particle filter algorithm evaluation method is further used to optimize the defect of the English speech rationality and high recognition error rate Related experiments have verified the effectiveness of the method.…”
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Application of Optimal Scheduling Model Based on Improved Genetic Algorithm in Electric Power Mobile Operation
Published 2024-01-01“…In order to solve the current situation, an optimized scheduling model for power mobile jobs based on improved genetic algorithm is proposed. …”
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Anti-Collision Path Planning and Tracking of Autonomous Vehicle Based on Optimized Artificial Potential Field and Discrete LQR Algorithm
Published 2024-11-01“…Comparative analysis of visual trajectories pre-optimization and post-optimization highlights improvements. …”
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Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization Algorithm
Published 2022-01-01“…The parametric mathematical model of the airfoil and aerodynamic parameter proxy model of airfoil were constructed using the Hicks-Henne improved function and CFD solution sample, focusing on the issues with particle swarm optimization algorithms such as slow convergence, a tendency to fall into local optimal solutions, and oscillation at a late stage; an optimization method for the low-speed airfoil of a small UAV based on improved particle swarm optimization was developed. …”
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Optimal Operation of Microgrid Based on Improved Particle Swarm Optimization Algorithm
Published 2020-05-01“…Under same conditions, the optimal operation model of the microgrid is solved using the original algorithm and the improved algorithm respectively, and the superiority of the improved algorithm is verified by comparing the solution results.…”
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Research on Interference Resource Optimization Based on Improved Whale Optimization Algorithm
Published 2025-01-01“…Then, in the solution process, to address the issues of the Whale Optimization Algorithm (WOA) easily falling into local optima and low convergence accuracy, the BIO-WOA (Bernoulli Chaotic mapping In-nonlinear Factors and Opposition-based Learning Improved Whale Optimization Algorithm, BIO-WOA) is proposed. …”
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A novel research on network security situation prediction based on iteratively optimized RBF-NN
Published 2025-05-01“…Moreover, we introduce a cross-model method with a genetic algorithm to compute the optimal weights for the RBF-NN model. …”
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Designing a new optimal controller for a PEMFC by an improved design of the Coot Optimizer
Published 2025-05-01Subjects: Get full text
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Integrated optimization model for production and equipment dispatching in underground mines
Published 2018-09-01“…The model was validated in a large gold mine in China to work out the optimal equipment scheduling plan. …”
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THE ALGORITHMIC MODEL OF LABORATORY DIAGNOSTICS OPTIMIZATION
Published 2015-12-01“…Various algorithmic models, their features and structure are reviewed. …”
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DESIGN HYBRID META-HEURISTIC APPROACHES FOR IMPROVED RELIABILITY OPTIMIZATION
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Primary Frequency Regulation Modeling of Deep Peak Regulation Unit Based on Improved Group Optimization Algorithm
Published 2020-06-01“…Then the unknown parameter values in the model are derived by using an improved group optimization algorithm with better global search capability. …”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024-12-01“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Solving UAV 3D Path Planning Based on the Improved Lemur Optimizer Algorithm
Published 2024-10-01Subjects: Get full text
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Parameter Optimization of MALDI-TOF MS Based on Improved Whale Optimization Algorithm
Published 2025-05-01“…To address the shortcomings of the Whale optimization algorithm, including slow convergence speed, low precision and susceptibility to local optima, improvements were made on the convergence factor, inertia weight and position update strategy. …”
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Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting
Published 2025-01-01“…To evaluate the predictive capability, the models are compared with quantum bee colony algorithm-optimized AI models (QABC-SVR and QABC-ANN), genetic algorithm-optimized AI models (GA-SVR and GA-ANN) and traditional AI models (SVR and ANN). …”
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Improved grey wolf optimization algorithm based service function chain mapping algorithm
Published 2022-11-01“…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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