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Chang Guo, Jianfeng Zhu and Xiaoming Wang
In recent years, the rapid growth of vehicles has imposed a significant burden on urban road resources. To alleviate urban traffic congestion in intelligent transportation systems (ITS), real-time and accurate traffic flow prediction has emerged as an ef...
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Lei Fu, Tiantian Zhu, Guobing Pan, Sihan Chen, Qi Zhong and Yanding Wei
Power quality disturbances (PQDs) have a large negative impact on electric power systems with the increasing use of sensitive electrical loads. This paper presents a novel hybrid algorithm for PQD detection and classification. The proposed method is cons...
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Nan Zhang, Xueyi Gao and Tianyou Yu
Attribute reduction is a challenging problem in rough set theory, which has been applied in many research fields, including knowledge representation, machine learning, and artificial intelligence. The main objective of attribute reduction is to obtain a ...
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O. V. Shcherbina,A. G. Shibaev
Pág. 112 - 120
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Tanja Vonach, Franz Tscheikner-Gratl, Wolfgang Rauch and Manfred Kleidorfer
Although calibration of a hydrodynamic model depends on the availability of measurement data representing the system behavior, advice for the planning of necessary measurement campaigns for model calibration is scarce. This work tries to address this que...
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Tanja Vonach, Franz Tscheikner-Gratl, Wolfgang Rauch and Manfred Kleidorfer
Although calibration of a hydrodynamic model depends on the availability of measurement data representing the system behavior, advice for the planning of necessary measurement campaigns for model calibration is scarce. This work tries to address this que...
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Kaan Yilmaz and Neil Yorke-Smith
In line with the growing trend of using machine learning to help solve combinatorial optimisation problems, one promising idea is to improve node selection within a mixed integer programming (MIP) branch-and-bound tree by using a learned policy. Previous...
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Haoxiang Xu, Tongyao Ren, Zhuangda Mo and Xiaohui Yang
Since the classification methods mentioned in previous studies are currently unable to meet the accuracy requirements for fault diagnosis in large-scale chemical industries, these methods are gradually being eliminated and rarely used. This research offe...
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Zahid Khan, Anis Koubaa, Sangsha Fang, Mi Young Lee and Khan Muhammad
The reliability, scalability, and stability of routing schemes are open challenges in highly evolving vehicular ad hoc networks (VANETs). Cluster-based routing is an efficient solution to cope with the dynamic and inconsistent structure of VANETs. In thi...
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Edvaldo Domingos, Blessing Ojeme and Olawande Daramola
Until recently, traditional machine learning techniques (TMLTs) such as multilayer perceptrons (MLPs) and support vector machines (SVMs) have been used successfully for churn prediction, but with significant efforts expended on the configuration of the t...
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Fedor Krasnov,Alexander Butorin
Pág. 21 - 27
The authors continue to study the application of machine learning methods to Geophysics problems. The focus of this work was the procedure for selecting frequencies for RGB-mixing. Previous work of the authors in this direction used a heuristic app...
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Wende Li, Haowen Yan, Xiaomin Lu and Yilang Shen
Building displacement is a common operation to resolve the spatial conflicts between map features, and it has important theoretical value and practical application significance for multi-scale mapping. The prerequisite for a successful displacement opera...
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Martin Fraga, Matías Micheletto, Andrés Llinás, Rodrigo Santos and Paula Zabala
Flow scheduling in Data Center Networks (DCN) is a hot topic as cloud computing and virtualization are becoming the dominant paradigm in the increasing demand of digital services. Within the cost of the DCN, the energy demands associated with the network...
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Imre Czinege
Pág. 75 - 79
The paper deals with the mass optimization of gear pairs. The proposed material science based selection strategy uses an extended version of Ashby model, where the minimum value of mass as function of material parameters and density can be calculated. Co...
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Rafael Lahoz-Beltra
Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i.e., mutation, crossover, etc. and population dynamical proce...
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Chuanwei Zhang, Xinyue Yang, Rui Zhou and Zhongyu Guo
In order to solve the problem of low safety and efficiency of underground mine vehicles, a path planning method for underground mine vehicles based on an improved A star (A*) and fuzzy control Dynamic Window Approach (DWA) is proposed. Firstly, the envir...
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Enrique Díaz de León-Hicks, Santiago Enrique Conant-Pablos, José Carlos Ortiz-Bayliss and Hugo Terashima-Marín
In the algorithm selection problem, where the task is to identify the most suitable solving technique for a particular situation, most methods used as performance mapping mechanisms have been relatively simple models such as logistic regression or neural...
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Liming Guo, Jian Du, Jianfeng Zheng and Nan He
In the shipping network optimization, the feeder liner companies not only need to decrease the operation cost by comprehensively optimizing the route, schedule, and fleet but also try to increase the operation income by attracting more shippers, with mul...
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Yuanzi Zhang, Jing Wang, Xiaolin Li, Shiguo Huang and Xiuli Wang
There are generally many redundant and irrelevant features in high-dimensional datasets, which leads to the decline of classification performance and the extension of execution time. To tackle this problem, feature selection techniques are used to screen...
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Qingni Yuan, Junhui Yi, Ruitong Sun and Huan Bai
To improve the path planning efficiency of a robotic arm in three-dimensional space and improve the obstacle avoidance ability, this paper proposes an improved artificial potential field and rapid expansion random tree (APF-RRT) hybrid algorithm for the ...
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