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Wen Cao, Jiaqi Xu, Yong Zhang, Siqi Zhao, Chu Xu and Xiaofeng Wu
The artificial bee colony algorithm (ABC) is a promising metaheuristic algorithm for continuous optimization problems, but it performs poorly in solving discrete problems. To address this issue, this paper proposes a hybrid discrete artificial bee colony...
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Yue Hu, Yunzhe Jiang, Yinqiu Liu and Xiaoming He
UAVs can be deployed in many scenarios to provide various types of services via 6G edge communication. In these scenarios, it is necessary to obtain the position of the UAVs in a timely and accurate manner to avoid UAV collisions. In this paper, we consi...
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Ekaterina Antipova and Sergey Rashkovskiy
Within the framework of the mathematical theory of conflicts, we consider a multi-criterial conflict situation using the example of a child?parent conflict. A general method for constructing a conflict diagram is described and possible ways of the confli...
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Xinxin Zhou, Yujie Chen, Yingying Li, Bingjie Liu and Zhaoyuan Yu
As a kind of first aid healthcare service, emergency medical services (EMSs) present high spatiotemporal sensitivity due to significant changes in the time-dependent urban environment. Taking full advantage of big spatiotemporal data to realize multiperi...
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Nikolay Nefedov, Bogdan Tishchenko and Natalia Levashova
An algorithm is presented for the construction of an asymptotic approximation of a stable stationary solution to a diffusion equation system in a two-dimensional domain with a smooth boundary and a source function that is discontinuous along some smooth ...
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Faisal Baig, Mohsen Sherif and Muhammad Abrar Faiz
Mountainous watersheds have always been a challenge for modelers due to large variability and insufficient ground observations, which cause forcing data, model structure, and parameter uncertainty. This study employed Differential Evolution Adaptive Metr...
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Qibing Jin, Nan Lin and Yuming Zhang
K-Means Clustering is a popular technique in data analysis and data mining. To remedy the defects of relying on the initialization and converging towards the local minimum in the K-Means Clustering (KMC) algorithm, a chaotic adaptive artificial bee colon...
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Wilson Tsakane Mongwe, Rendani Mbuvha and Tshilidzi Marwala
Markov chain Monte Carlo (MCMC) techniques are usually used to infer model parameters when closed-form inference is not feasible, with one of the simplest MCMC methods being the random walk Metropolis?Hastings (MH) algorithm. The MH algorithm suffers fro...
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Qiao Yan, Xiaoqian Liu, Xiaoping Deng, Wei Peng and Guiqing Zhang
Prediction of energy use behaviors is a necessary prerequisite for designing personalized and scalable energy efficiency programs. The energy use behaviors of office occupants are different from those of residential occupants and have not yet been studie...
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Hesheng Tang, Xueyuan Guo, Liyu Xie and Songtao Xue
The uncertainty in parameter estimation arises from structural systems? input and output measured errors and from structural model errors. An experimental verification of the shuffled complex evolution metropolis algorithm (SCEM-UA) for identifying the o...
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