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Št. zadetkov: 3
ǂAn ǂimproved discrete particle swarm optimization approach for a multi-objective optimization model of an urban logistics distribution network considering traffic congestion
K. Li, D. Li, H. Q. Ma
Izvirni znanstveni članek
Oznake: distribucijsko omrežje mestne logistike;modeliranje;inteligenca roja;urban logistics distribution network;traffic congestion;optimization;modelling;multi-objective optimization;vehicle routing problem;VRP;swarm intelligence;discrete particle swarm optimization algorithm;DPSO;
To optimize urban logistics networks, this paper proposes a multi-objective optimization model for urban logistics distribution networks (ULDN). The model optimizes vehicle usage costs, transportation costs, penalty costs for failing to meet time windows, and carbon emission costs, while also consid ...
Leto: 2023 Vir: Digitalna knjižnica Univerze v Mariboru (DKUM)
Using the gradient boosting decision tree (GBDT) algorithm for a train delay prediction model considering the delay propagation feature
Y. D. Zhang, L. Liao, Q. Yu, W. G. Ma, K. H. Li
Izvirni znanstveni članek
Oznake: napoved zamud vlakov;podatki o dejanskem obratovanju vlakov;identifikacija tipa zakasnitve;ekstrakcija značilnosti širjenja zakasnitve;prostorsko združevanje aplikacij s šumom na podlagi gostote;naključni gozd;regresija podpornih vektorjev;train delay prediction;actual train operation data;delay type identification;delay propagation feature extraction;density-based spatial clustering of applications with noise (DBSCAN);k-nearest neighbor (KNN);gradient boosting decision tree (GBDT);random forest (RF);support vector regression (SVR);multilayer perceptron (MLP);
Accurate prediction of train delay is an important basis for the intelligent adjustment of train operation plans. This paper proposes a train delay prediction model that considers the delay propagation feature. The model consists of two parts. The first part is the extraction of delay propagation fe ...
Leto: 2021 Vir: Digitalna knjižnica Univerze v Mariboru (DKUM)
Optimizing abrasive water jet milling of alumina ceramics with RBF neural networks
Y.T. Feng, Z.R. Shi, X. Yang, W. Huang, X. Luo, Y.H. Li, L. Yu
Izvirni znanstveni članek
Oznake: abrazivni vodni curek;rezkanje;natančna obdelava;abrasive water jet;AWJ;milling;alumina ceramic;precisio machining;material removal rate;single-factor experiment;orthogonal array;RFB neural network;
Abrasive water jet technology is an advanced machining method that combines high-pressure water jet with solid abrasives. Owing to its unique coldprocessing characteristics, high flexibility, and environmental bebefits, it has been widely applied in aerospace, medical devices, microelectronics, defe ...
Leto: 2025 Vir: Digitalna knjižnica Univerze v Mariboru (DKUM)
Št. zadetkov: 3
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