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1981
Development of Model for Traffic Flows on Urban Street and Road Network
Published 2019-02-01“…The developed model has a complex structure of algorithmic support. …”
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1982
Establishment and Solution Test of Wear Prediction Model Based on Particle Swarm Optimization Least Squares Support Vector Machine
Published 2025-03-01“…Experimental results show that the PSO-LS-SVM model shows high accuracy and good performance in tool wear state identification, which verifies the effectiveness of the algorithm in improving tool efficiency and extending tool life. …”
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1983
Production Dynamic of Coal-bed Methane After Well Pressure Based on Multi-layer Perceptron Model Inversion Study
Published 2023-10-01“…The inversion of production performance after fracturing of coal-bed methane well is the key technology to realize the efficient development of gas reservoir. In order to improve the inversion efficiency of traditional numerical simulation methods, with the help of machine learning modeling technology and intelligent algorithm, this paper studies the automatic inversion and programmed design of key parameters such as coal-bed methane reservoir matrix permeability, gas saturation, fracture half length, fracture number and fracture conductivity. …”
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1984
Modeling and Performance Evaluation of Hybrid Classical–Quantum Serverless Computing Platforms
Published 2025-01-01“…In this work, we define a system model for a hybrid classical–quantum serverless system, with an associated open-source numerical simulator that can be driven by production traces and stochastic workload models. …”
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1985
Research on the Capability Maturity Evaluation of Intelligent Manufacturing Based on Firefly Algorithm, Sparrow Search Algorithm, and BP Neural Network
Published 2021-01-01“…In order to overcome the shortcoming of SSA that it is easy to fall into the local optimum, the firefly disturbance strategy is introduced to improve it, a new sparrow search algorithm (FASSA) is proposed, and on this basis, an intelligent manufacturing capability maturity evaluation model based on the FASSA-BP algorithm is constructed. …”
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1986
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. The system was modeled based on a state-space mathematical representation and simulated using MATLAB. …”
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1987
Enhancing crane and gate OCR efficiency at container terminal using a hybrid genetic algorithm and neural network model: case study of tangier med port
Published 2025-07-01“…The research incorporates a hybrid GA-Neural Network (NN) model further, using machine learning to speed up fitness evaluation and provide optimal settings for OCR performance improvement that is applicable in real world. …”
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1988
A novel ensemble learning algorithm integrating WRF-CMAQ and downscaling models for hourly estimation of regional air pollution along with vegetation exposure risk detection
Published 2025-08-01“…To achieve this, an integrated machine learning algorithm was developed by coupling the Weather Research and Forecasting-Community Multiscale Air Quality model with a downscaling model to estimate air pollutants during compound pollution episodes in Beijing. …”
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1989
A novel approach for efficient resource allocation in 6G V2V networks using neighbor-aware greedy algorithm and sweep line model
Published 2025-06-01“…In our research, we present an Enhanced Neighbor Node Associated Greedy-based Resource Distributed V2V Model with Sweep Line Model (NNAGbRD-V2V-SLM) for secure resource handling and management in V2V and V2X communication. …”
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1990
Time-Variation Damping Dynamic Modeling and Updating for Cantilever Beams with Double Clearance Based on Experimental Identification
Published 2025-01-01“…Finally, a case study is conducted to verify the presented model. In comparison with the initial dynamic model based on constant damping, the modal assurance criterion (MAC) of the proposed improved model based on time-variation damping is improved by 43.97%, the mean relative error (MRE) of the frequency response function (FRF) is reduced by 32.6%, and the root mean square error (RMSE) is reduced by 18.19%. …”
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1991
RF-SFAD: A RANDOM FOREST MODEL FOR SELECTIVE FORWARDING ATTACK DETECTION IN MOBILE WIRELESS SENSOR NETWORKS
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1992
Modeling of cross line operation of urban rail transit trains based on passenger travel time
Published 2022-09-01“…The model is solved by genetic algorithm. The scheme of metro Line Ⅰ of city S crossing into Line Ⅱ is used as an example to verify the feasibility of the model, and the optimal train density under different train load rates is obtained. …”
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1993
An Adaptive Task Traffic Shaping Method for Highly Concurrent Geographic Information System Services with Limited Resources
Published 2025-04-01“…This paper proposes an adaptive task traffic shaping method to improve the utilization efficiency of server resources, reduce task processing delay, and improve service stability and response speed by monitoring the system load in real time and dynamically adjusting the processing rate of GIS task traffic. …”
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1994
Low-carbon optimization planning method for integrated energy system based on DG uncertainty affine model
Published 2024-08-01“…Then, based on the differential evolution-particle swarm optimization algorithm, the established low-carbon planning model of the integrated energy system was solved to avoid the algorithm from falling into local optimality during the optimization process. …”
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1995
Wavelet Decomposition-Based AVOA-DELM Model for Prediction of Monthly Runoff Time Series and Its Applications
Published 2022-01-01“…For the improvement in prediction accuracy of monthly runoff time series,a prediction model is proposed,which combines the wavelet decomposition (WD),African vultures optimization algorithm (AVOA),and deep extreme learning machine (DELM),and it is applied to the monthly runoff prediction of Yale Hydrological Station in Yunnan Province.Specifically,WD decomposes the time-series data of monthly runoff to obtain highly regular subsequence components,and AVOA is employed to optimize the number of neurons in the hidden layers of DELM;then,the WD-AVOA-DELM model is built to predict each subsequence component,and the prediction results are summated and reconstructed to produce the final prediction results of monthly runoff.Meanwhile,models based on the support vector machine (SVM) and BP neural networks are constructed for comparative analysis,including WD-AVOA-SVM,WD-AVOA-BP,AVOA-DELM,AVOA-SVM,and AVOA-BP models.The results reveal that the average absolute percentage error of the WD-AVOA-DELM model for the monthly runoff prediction of Yale Hydrological Station is 3.02%;the prediction error is far less than that of WD-STOA-SVM and WD-AVOA-BP models,and the prediction accuracy is more than one order of magnitude higher than that of AVOA-SVM,AVOA-SVM,and AVOA-BP models.The result indicates that the proposed model has good prediction performance.In this model,WD can scientifically reduce the complexity of runoff series and raise the prediction accuracy;AVOA can effectively optimize the key parameters of DELM and improve the performance of DELM networks.…”
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1996
A hybrid bio-inspired augmented with hyper-parameter deep learning model for brain tumor classification
Published 2025-07-01“…To further improve the performance of the model, SSA was increased to select relevant features. …”
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1997
Transient Stability Analysis of Wind-Integrated Power Systems via a Kuramoto-like Model Incorporating Node Importance
Published 2025-06-01“…First, virtual node technology is utilized to optimize the power grid topology model. Then an improved PageRank algorithm embedded by a critical node identification method is proposed, which simultaneously considers transmission efficiency, coupling transmission probability, and voltage influence among nodes. …”
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1998
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1999
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2000
A Deformation Prediction Model for Concrete Dams Based on RSA-VMD-AttLSTM
Published 2025-01-01“…Analysis of the five evaluation criteria revealed that the RSA can better optimize the parameters of the VMD algorithm. Consequently, the proposed model demonstrates superior noise reduction capabilities and improved prediction accuracy.…”
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