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1901
Similar Instances Reuse Based Numerical Control Process Decision Method for Prismatic Parts
Published 2025-01-01“…The NC process decision efficiency is improved by 84.6%. On the other hand, the manufacturing cost of the optimal NC process scheme is 16.6% lower.Conclusions The experimental results showed that the proposed approach can generate optimal NC process schemes for parts effectively and automatically, decrease production costs, and shorten the development cycle. …”
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1902
Influence of artificial intelligence on higher education reform and talent cultivation in the digital intelligence era
Published 2025-02-01“…Abstract In order to solve the problems of inefficient allocation of teaching resources and inaccurate recommendation of learning paths in higher education, this paper proposes a smart education optimization model (SEOM) by combining the improved random forest algorithm (RFA) based on adaptive enhancement mechanism and the Graph Neural Network (GNN) algorithm. …”
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1903
Spatio‐temporal dynamic navigation for electric vehicle charging using deep reinforcement learning
Published 2024-12-01“…A recently proposed on‐policy actor–critic method, phasic policy gradient (PPG) which extends the proximal policy optimization algorithm with an auxiliary optimization phase to improve training by distilling features from the critic to the actor network, is used to make EVCS decisions on the network where EV travels through the optimal path from origin node to EVCS by considering dynamic traffic conditions, unit value of EV owner and time‐of‐use charging price. …”
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1904
Towards load adaptive routing based on link critical degree for delay-sensitive traffic in IP networks
Published 2015-03-01“…Firstly, an optimization objective function has been put forward; and then decomposed into several sub-functions by using convex optimization theory; finally, the optimization objective function and sub-functions were transformed into a simple distributed protocol. …”
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1905
Movie Box Office Prediction Based on IFOA-GRNN
Published 2022-01-01“…The contribution of this article is to propose a generalized regression neural network model based on an improved fruit fly optimization algorithm, which can greatly improve the accuracy of movie box office prediction.…”
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1906
Vehicle Routing Problem for Collaborative Multidepot Petrol Replenishment under Emergency Conditions
Published 2021-01-01“…As a method to solve the model, genetic variation of multiobjective particle swarm optimization algorithm is considered. The effectiveness of the proposed method is analyzed and verified by first using a small-scale example and then investigating a regional multidepot petrol distribution network in Chongqing, China. …”
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1907
Interfered feature elimination coupled with feature group selection for wound infection detection by electronic nose.
Published 2025-01-01“…As the precise odor-sensing equipment, the electronic nose integrates multiple advanced and sensitive sensors that can identify wound infections non-invasively and rapidly by analyzing wound characteristic odor. To reduce the cost of sensors and improve or maintain e-nose's performance, efficient optimization of sensor arrays is required. …”
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1908
Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds
Published 2025-06-01“…Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). …”
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1909
Constrained total least squares localization using angle of arrival and time difference of arrival measurements in the presence of synchronization clock bias and sensor position er...
Published 2019-07-01“…Based on measurements of angle of arrival and time difference of arrival, a method is proposed to improve the accuracy of localization with imperfect sensors. …”
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1910
Integrated Planning for Shared Electric Vehicle System Considering Carbon Emission Reduction
Published 2024-12-01“…By applying these models to the Chicago Sketch network and using a genetic algorithm to solve the models, it is concluded that the optimal outlet location solution considering carbon emission reduction will increase the outlet construction cost and user travel time cost. …”
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1911
Research on the cooperative offloading strategy of sensory data based on delay and energy constraints
Published 2023-03-01“…The edge offloading of the internet of things (IoT) sensing data was investigated.Multiple edge servers cooperatively offload all or part of the sensing data initially sent to the cloud center, which protects data privacy and improves user experience.In the process of cooperative offloading, the transmission of the sensing data and the information exchange among edge servers will consume system resources, resulting in the cost of cooperation.How to maximize the offloading ratio of the sensing data while maintaining a low collaboration cost is a challenging problem.A joint optimization problem of sensing data offload ratio and cooperative scale satisfying the constraints of network delay and system energy consumption was formulated.Subsequently, a distributed alternating direction method of multipliers (ADMM) via constraint projection and variable splitting was proposed to solve the problem.Finally, simulation experiments were carried out on MATLAB.Numerical results show that the proposed method improved the network delay and energy consumption compared to the fairness cooperation algorithm (FCA), the distributed optimization algorithm (DOA), and multi-subtasks-to-multi-servers offloading scheme (MTMS) algorithm.…”
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1912
Orchard Navigation Method Based on RS-SC Loop Frame Search Method and SLAM Technology
Published 2025-01-01“…In the loop frame matching, an optimization algorithm combining normal distribution transformation and iterative nearest point is used to reduce the cumulative error significantly. …”
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1913
Outdoor location scheme with fingerprinting based on machine learning of mobile cellular network
Published 2021-08-01“…The positioning scheme based on mobile cellular network technology is one of the important technical approaches to provide network optimization, emergency rescue, police patrol and location services.The traditional positioning scheme based on cell base station location information has low positioning accuracy and large positioning error, so it cannot meet the requirements of some positioning applications.The scheme based on fingerprint location can greatly improve the location accuracy, save computational cost and enhance the usability based on the coarse location scheme of the cell and become the hotspot of the research.Rasterization and non-rasterization of outdoor fingerprint location scheme based on machine learning were studied and analyzed to meet the business requirements of outdoor fingerprint location.By means of parameter weighting, data fitting and other methods, large-scale fingerprint data were cleaned to improve the effectiveness of data sources.Through the realization of sub-modules such as demarcating research area, rasterizing, constructing fingerprint database, training model, correcting model, non-rasterizing, rough positioning coupling, matching parameter and training parameter, the operation efficiency and positioning accuracy of the algorithm were analyzed and optimized, and the key indexes affecting the algorithm performance were determined.Then, the performance of two fingerprint-based localization schemewas analyzed based on the simulation results.Finally, the typical scenarios of the fingerprint location scheme based on machine learning in practical application were presented.…”
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1914
Distributed Multi-Energy Trading in Energy Internet: An Aggregative Game Approach
Published 2025-01-01“…Since each WE only needs to communicate with its neighbors to exchange information, this distributed process reduces communication burden and improves information security. Furthermore, a multi-energy transmission optimization model is established to determine the transmission path of the transmission energy, which can minimize the transmission cost. …”
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1915
Broad learning system based on attention mechanism and tracking differentiator
Published 2024-09-01“…In terms of model structure, A-TD-BLS introduced self-attention mechanism to the original BLS, and further fused and transformed the extracted features through attention weighting to improve the feature learning ability.In terms of model training methods, a weight optimization algorithm based on tracking differentiator was designed.This method effectively alleviates the overfitting phenomenon of the original BLS by limiting the size of the weight values, significantly reduces the influence of the number of hidden layer nodes on model performance and makes the generalization performance more stable.Moreover, the training algorithm was extended to the BLS incremental learning framework, so that the model can improve performance by dynamically adding hidden layer nodes.Multiple experiments conducted on some benchmark datasets show that compared to the original BLS, the classification accuracy of A-TD-BLS is increased by 1.27% on average on classification datasets and the root mean square error of A-TD-BLS is reduced by 0.53 on average on regression datasets.Besides, A-TD-BLS is less affected by the number of hidden layer nodes and has more stable generalization performance. …”
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1916
A dynamic service migration strategy based on mobility prediction in edge computing
Published 2021-02-01“…Furthermore, we build a network model and propose a based on Lyapunov optimization method with long-term cost constraints. …”
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1917
Research on Short-Term Load Forecasting of LSTM Regional Power Grid Based on Multi-Source Parameter Coupling
Published 2025-01-01“…In order to further optimize the performance of the LSTM model, the IPSO algorithm, and linear difference decreasing inertia weight are introduced to improve the global optimization ability and convergence speed of the PSO algorithm and reduce the risk of local optimal solutions. …”
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1918
Investigation on the Role of Artificial Intelligence in Measurement System
Published 2025-01-01“…Hardware approach with soft computation has reduced non linearity error by 84.63% for thermocouple linearization, meanwhile novel hybrid approach using genetic algorithm (GA) and particle swarm optimization (PSO) combined with back propagation neural network (BPNN) have reduced mean absolute percentage error to 1.2 % for industrial weir than conventional hardware approaches using sensors and signal conditioning circuits but at higher computational cost. …”
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1919
Investigation on Photovoltaic Array Modeling and the MPPT Control Method under Partial Shading Conditions
Published 2021-01-01“…The experimental results show that the PV optimizer improves the output power of the PV modules by 13.4% under the PSC.…”
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1920
Computation Offloading and Resource Allocation for Energy-Harvested MEC in an Ultra-Dense Network
Published 2025-03-01“…In this study, issues related to computation offloading and resource allocation are addressed using the Lyapunov mixed-integer linear programming (MILP)-based optimal cost (LYMOC) technique. The optimization problem is solved using the Lyapunov drift-plus-penalty method. …”
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