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Št. zadetkov: 7
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)
Privacy-preserving AI-based framework for container transportation demand forecasting in sea-rail intermodal systems
L. Huang, D. Y. Jiang, T. Bai
Izvirni znanstveni članek
Oznake: prevoz tovora;kontejnerski transport;napovedovanje transportnih zahtev;razporejanje;umetna inteligenca;strojno učenje;intermodalni transport;freight demand forecasting;container transportation demand forecasting;vertical federated learning;privacy-preserving methods;sample and feature selection;machine learning;homomorphic encryption;resource allocation and scheduling;
In response to the growing demand for accurate freight forecasting in sea-rail intermodal transportation, particularly under the constraints of stringent data protection regulations, we introduce a privacy-preserving, AI-based framework that focuses on the micro-level identification of container tra ...
Leto: 2025 Vir: Digitalna knjižnica Univerze v Mariboru (DKUM)
Improved genetic algorithm (VNS-GA) using polar coordinate classification for workload balanced multiple traveling salesman problem (mTSP)
Y. D. Wang, X. C. Lu, J. R. Shen
Izvirni znanstveni članek
Oznake: problem več potujočih prodajalcev;ravnovesje delovne obremenitve;algoritem za iskanje spremenljive soseske;genetski algoritmi;polarne koordinate;klasifikacija;multiple traveling salesman problem (mTSP);workload balance;variable neighbourhood search algorithm (VNS);genetic algorithm (GA);polar coordinates;classification;
GThe multiple traveling salesman problem (mTSP) is an extension of the traveling salesman problem (TSP), which has wider applications in real life than the traveling salesman problem such as transportation and delivery, task allocation, etc. In this paper, an improved genetic algorithm (VNS-GA) that ...
Leto: 2021 Vir: Digitalna knjižnica Univerze v Mariboru (DKUM)
Clustering patterns in efficiency and the coming-of-age of the cryptocurrency market
Higor Y. D. Sigaki, Matjaž Perc, Haroldo V. Ribeiro
Izvirni znanstveni članek
Oznake: kriptovalute;tržna učinkovitost;finančno trgovanje;fizika družbe;cryptocurrency;market efficiency;financial trading;social physics;
The efficient market hypothesis has far-reaching implications for financial trading and market stability. Whether or not cryptocurrencies are informationally efficient has therefore been the subject of intense recent investigation. Here, we use permutation entropy and statistical complexity over sli ...
Leto: 2019 Vir: Fakulteta za naravoslovje in matematiko (UM FNM)
Monte Carlo Tree Search improved Genetic Algorithm for unmanned vehicle routing problem with path flexibility
Y. D. Wang, X. C. Lu, Y. M. Song, Y. Feng, J. R. Shen
Izvirni znanstveni članek
Oznake: unmanned vehicle;path flexibility;vehicle routing problem;Genetic Algorithm;GA;Monte Carlo Tree Search algorithm;MCTS;COVID-19;pandemics;
With the gradual normalization of the COVID-19, unmanned delivery has gradually become an important contactless distribution method around China. In this paper, we study the routing problem of unmanned vehicles considering path flexibility and the number of traffic lights in the road network to redu ...
Leto: 2022 Vir: Digitalna knjižnica Univerze v Mariboru (DKUM)
Collective dynamics of stock market efciency
Luiz G. A. Alves, Higor Y. D. Sigaki, Matjaž Perc, Haroldo V. Ribeiro
Izvirni znanstveni članek
Oznake: kolektivna dinamika;fizika družbe;ekonofizika;borzni trg;collective dynamics;social physics;econophysics;stock market;
Summarized by the efcient market hypothesis, the idea that stock prices fully refect all available information is always confronted with the behavior of real-world markets. While there is plenty of evidence indicating and quantifying the efciency of stock markets, most studies assume this efciency t ...
Leto: 2020 Vir: Fakulteta za naravoslovje in matematiko (UM FNM)
Learning physical properties of liquid crystals with deep convolutional neural networks
Higor Y. D. Sigaki, Ervin K. Lenzi, Rafael S. Zola, Matjaž Perc, Haroldo V. Ribeiro
Izvirni znanstveni članek
Oznake: tekoči kristal;nevronska mreža;umetna inteligenca;mehka snov;liquid crystal;neural network;artificial intelligence;soft matter;
Machine learning algorithms have been available since the 1990s, but it is much more recently that they have come into use also in the physical sciences. While these algorithms have already proven to be useful in uncovering new properties of materials and in simplifying experimental protocols, their ...
Leto: 2020 Vir: Fakulteta za naravoslovje in matematiko (UM FNM)
Št. zadetkov: 7
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