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Optimization method of time of use electricity price considering losses in distributed photovoltaic access distribution network
Published 2025-01-01“…And refer to the basic requirements for electricity pricing in the distribution network, set a series of constraints for optimizing electricity prices. Applying an improved imperialist competition algorithm this paper integrates Tent chaotic reverse learning to solve a multi-objective optimization model and obtain an optimized time of use electricity pricing plan. …”
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622
Grey modeling method for approximate exponential sequence of optimizing initial condition
Published 2016-11-01“…Grey GM(1,1)prediction method is only suitable for the prediction model of the original sequence which satisfies the characteristic of the approximate exponential through the accumulated generating operation.In order to widen the application range of the traditional grey prediction model,a new method,dubbed DGM(1,1,c,β)model(direct grey model),was proposed to improve the accuracy of grey GM(1,1)prediction by optimizing initial conditions.DGM(1,1,c,β)model was established for the original sequence conforming to the approximate exponential and the model parameters were obtained by the particle swarm optimization algorithm.Both the simulation and analysis of the example demonstrate that the proposed method is more effective and practical.…”
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623
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624
Solving the 3D Multi-Objective Dynamic AUV Path Planning Problem Based on the Improved Morphin-Altruistic NSGAII Algorithm
Published 2025-09-01“…To address these challenges, this paper proposes improved Morphin-Altruistic Nondominated Sorting Genetic Algorithm II (ANSGAII). …”
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625
Fuzzy Fault Tree Maintenance Decision Analysis for Aviation Fuel Pumps Based on Nutcracker Optimization Algorithm–Graph Neural Network Improvement
Published 2024-12-01“…Therefore, this paper proposes the NOA (Nutcracker Optimization Algorithm)–GNN (Graph Neural Network) model to enhance the accuracy and robustness of FTA by mitigating the uncertainty and inconsistency in expert knowledge. …”
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626
Review of optimization modeling and solution of long-distance natural gas pipeline network
Published 2023-09-01“…The optimization of the natural gas pipeline network is of great significance to reduce the operating cost of the pipeline network and improve the reliability of the natural gas supply. …”
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627
Improving crop rotation classification using a random forest model incorporating spatial heterogeneity
Published 2024-01-01Get full text
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628
A Water Quality Prediction Model Based on Long Short-Term Memory Networks and Optimization Algorithms
Published 2024-01-01“…In comparison with the previous prediction models such as SVR, LSTM, CNN-LSTM and CNN-GRU, obviously, the prediction effect of AWPSO-LSTMAT is significantly improved by means of modifying and optimizing the original algorithm. …”
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629
First-principle modeling of parallel-flow regenerative kilns and their optimization with genetic algorithm and gradient-based method
Published 2024-12-01“…Finally, we use a genetic algorithm to optimize the feed mass flows such that the conversion and the fuel efficiency are improved in a Pareto-optimal manner. …”
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630
Behavioral Modeling of SiC MOSFET Static and Dynamic Characteristics Based on Particle Swarm Optimization Algorithm
Published 2025-01-01“…This study proposes a SiC MOSFET behavioral model with parasitic parameters based on the particle swarm optimization (PSO) algorithm. …”
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631
Development of Hybrid Optimization Model Using Grey-ANFIS-Jaya Algorithm for CNC Drilling of Aluminium Alloy
Published 2024-01-01“…Statistical error analysis is used to estimate the performance of the established optimization model. Based on the investigative outcomes, the best-suited process variable combinations will be used to provide improved and enhanced multiperformance characteristics.…”
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632
Identification method of canned food for production line sorting robot based on improved PSO-SVM
Published 2023-10-01“…By improving the particle swarm optimization algorithm to optimize support vector machine parameters, an optimized support vector machine classification model was obtained. …”
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633
Two-Layer Optimal Scheduling and Economic Analysis of Composite Energy Storage with Thermal Power Deep Regulation Considering Uncertainty of Source and Load
Published 2024-09-01“…The upper layer takes pumped storage as the optimization goal to improve net load fluctuation and the optimal peak load benefit; the lower layer takes the system’s total peak load cost as the optimization goal and obtains a day-before scheduling plan for the energy storage system, using an improved gray wolf algorithm to process it. …”
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634
Prediction of Mechanical Properties of Cotton Fibers by a BP Neural Network Model Optimized by Genetic Algorithm
Published 2024-12-01“…The first 850 items of this dataset were then utilized to train the designed BP, and the remaining 28 items were evaluated for error. Next, the model is parameterized using a genetic algorithm to reduce the overall network size, thus optimizing the fit. …”
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635
Optimizing anomaly detection models for edge IIoT with an enhanced firefly algorithm-based hyperparameter tuning strategy
Published 2025-09-01“…This work presents an Enhanced Firefly Algorithm (EFA) for optimizing the hyperparameters of ML models to enable effective and accurate threat detection in resource-constrained IIoT contexts, so addressing these challenges. …”
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636
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637
Data-Driven Optimization Method for Recurrent Neural Network Algorithm: Greenhouse Internal Temperature Prediction Model
Published 2024-10-01“…The optimal amount of data was determined to be between three and seven days, with an average model r<sup>2</sup> of 0.8811 and an RMSE of 2.056 for the gated recurrent unit algorithm. …”
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638
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CSO Intelligent Optimization of Drag Torque Parameters of Wet Brakes Based on the SSA-BP Approximate Model
Published 2024-07-01“…Compared with the traditional BP model, the prediction accuracy is obviously improved, which can meet the needs of practical engineering. …”
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640
Short-Term Electricity Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Improved Sparrow Search Algorithm–Convolutional Neural Netwo...
Published 2025-02-01“…Accurate power load forecasting plays an important role in smart grid analysis. To improve the accuracy of forecasting through the three-level “decomposition–optimization–prediction” innovation, this study proposes a prediction model that integrates complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the improved sparrow search algorithm (ISSA), a convolutional neural network (CNN), and bidirectional long short-term memory (BiLSTM). …”
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