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Guangzhong Liu, Sheng Zhang, Guojie Ma and Yipeng Pan
In order to solve the problem of many constraints and a complex navigation environment in the path planning of unmanned surface vehicles (USV), an improved sparrow search algorithm combining cubic chaotic map and Gaussian random walk strategy was propose...
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Jing Hou, Xin Wang, Yanping Su, Yan Yang and Tian Gao
An accurate battery model is of great importance for battery state estimation. This study considers the parameter identification of a fractional-order model (FOM) of the battery, which can more realistically describe the reaction process of the cell and ...
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Zhenyu Song, Xuemei Yan, Lvxing Zhao, Luyi Fan, Cheng Tang and Junkai Ji
Brain-storm optimization (BSO), which is a population-based optimization algorithm, exhibits a poor search performance, premature convergence, and a high probability of falling into local optima. To address these problems, we developed the adaptive mecha...
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Nassime Aslimani, Talbi El-ghazali and Rachid Ellaia
Multi-objective optimization problems (MOPs) have been widely studied during the last decades. In this paper, we present a new approach based on Chaotic search to solve MOPs. Various Tchebychev scalarization strategies have been investigated. Moreover, a...
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Xuan Zhou, Yang Zheng, Bo Xu, Wushuang Liu, Yidong Zou and Jinbao Chen
Speed governing control is significant in ensuring the stable operation of pumped storage units. In this study, a state-space equation mathematical model of the pumped storage governing system considering the complex hydraulic pipeline structure of the p...
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Xianhao Shen, Zhaozhan Chang, Xiaolan Xie and Shaohua Niu
To reduce computing delay and energy consumption in the Vehicular networks, the total cost of task offloading, namely delay and energy consumption, is studied. A task offloading model combining local vehicle computing, MEC (Mobile Edge Computing) server ...
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Ke Chen, Bo Xiao, Chunyang Wang, Xuelian Liu, Shuning Liang and Xu Zhang
In today?s automation control systems, the PID controller, as a core technology, is widely used to maintain the system output near the set value. However, in some complex control environments, such as the application of ball screw-driven rotating motors,...
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Zitong Wang, Yan Pei and Jianqiang Li
The multi-objective optimization problem is difficult to solve with conventional optimization methods and algorithms because there are conflicts among several optimization objectives and functions. Through the efforts of researchers and experts from diff...
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Weili Liu, Jing Zhang, Wei Wei, Tao Qin, Yuanchen Fan, Fei Long and Jing Yang
The technology of wireless sensor networks (WSNs) is developing rapidly, and it has been applied in diverse fields, such as medicine, environmental control, climate prediction, monitoring, etc. Location is one of the critical fields in WSNs. Time differe...
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Long Chen, Diju Gao and Qimeng Xue
Reducing energy consumption and carbon emissions from ships is a major concern. The development of hybrid technologies offers a new direction for the rational distribution of energy. Therefore, this paper establishes a torque model for internal combustio...
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Linfeng Li, Weidong Liu, Le Li, Huifeng Jiao, Junqi Qu and Gongwu Sun
In order to solve the problem that the cesium optical pump magnetometer is disturbed by the carrier?s interference magnetic field during magnetic field anomaly detection, an interference magnetic field compensation method based on an improved mayfly opti...
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Baydaa Abdul Kareem, Salah L. Zubaidi, Hussein Mohammed Ridha, Nadhir Al-Ansari and Nabeel Saleem Saad Al-Bdairi
Accurate streamflow prediction is significant when developing water resource management and planning, forecasting floods, and mitigating flood damage. This research developed a novel methodology that involves data pre-processing and an artificial neural ...
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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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Ming-Wei Li, Jing Geng, Shumei Wang and Wei-Chiang Hong
Hybridizing evolutionary algorithms with a support vector regression (SVR) model to conduct the electric load forecasting has demonstrated the superiorities in forecasting accuracy improvements. The recently proposed bat algorithm (BA), compared with cla...
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Jafar Jafari-Asl, Seyed Arman Hashemi Monfared and Soroush Abolfathi
This study investigates the optimal and safe operation of pumping stations in water distribution systems (WDSs) with the aim of reducing the environmental footprint of water conveyance processes. We introduced the nonlinear chaotic honey badger algorithm...
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Chunguang Bi, Shuo Zhang, He Chen, Xinhua Bi, Jinjing Liu, Hao Xie, Helong Yu, Shaozhong Song and Lei Shi
Ensuring the security of germplasm resources is of great significance for the sustainable development of agriculture and ecological balance. By combining the morphological characteristics of maize seeds with hyperspectral data, maize variety classificati...
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Alkmini Michaloglou and Nikolaos L. Tsitsas
Brain storm optimization (BSO) and particle swarm optimization (PSO) are two popular nature-inspired optimization algorithms, with BSO being the more recently developed one. It has been observed that BSO has an advantage over PSO regarding exploration wi...
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Yufei Wang, Honghai Zhang, Zongbei Shi, Jinlun Zhou and Wenquan Liu
General aviation accidents have complex interactions and influences within them that cannot be simply explained and predicted by linear models. This study is based on chaos theory and uses general aviation accident data to conduct research on different t...
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