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Young Hwan Choi and Joong Hoon Kim
This study compares the performance of self-adaptive optimization approaches in efficient water distribution systems (WDS) design and presents a guide for the selection of the appropriate method employing optimization utilizing the characteristic of each...
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Yunia Reyes González, Alfonso Claro Arceo, Natalia Martínez Sánchez, Antonio Hernández Domínguez
Pág. 82 - 96
Solving a problem leads to a process of identification and selection of the appropriate route for it solution. This process is called Decision Making, where a decision is choosing one among several alternatives. The basis of the decision-making process i...
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Marko Ðurasevic, Domagoj Jakobovic, Stjepan Picek and Luca Mariot
The automated design of dispatching rules (DRs) with genetic programming (GP) has become an important research direction in recent years. One of the most important decisions in applying GP to generate DRs is determining the features of the scheduling pro...
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Yuzhu Zhang and Hao Xu
This study investigates the problem of decentralized dynamic resource allocation optimization for ad-hoc network communication with the support of reconfigurable intelligent surfaces (RIS), leveraging a reinforcement learning framework. In the present co...
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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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Jinhui Guo, Xiaoli Zhang, Kun Liang and Guoqiang Zhang
In recent years, the emergence of large-scale language models, such as ChatGPT, has presented significant challenges to research on knowledge graphs and knowledge-based reasoning. As a result, the direction of research on knowledge reasoning has shifted....
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Shuai Zheng, Yumin Su, Jiayuan Zhuang, Yueqi Tang and Guangjie Yi
The development of dynamic positioning (DP) algorithms for an unmanned surface vehicle (USV) is attracting great interest, especially in support of complex missions such as sea rescue. In order to improve the simplicity of the algorithm, a DP algorithm b...
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Broderick Crawford, Felipe Cisternas-Caneo, Katherine Sepúlveda, Ricardo Soto, Álex Paz, Alvaro Peña, Claudio León de la Barra, Eduardo Rodriguez-Tello, Gino Astorga, Carlos Castro, Franklin Johnson and Giovanni Giachetti
The digitization of information and technological advancements have enabled us to gather vast amounts of data from various domains, including but not limited to medicine, commerce, and mining. Machine learning techniques use this information to improve d...
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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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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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