Results 141 to 150 of about 1,795 (171)

Compact Harris Hawks Optimization Algorithm

2021 40th Chinese Control Conference (CCC), 2021
The intelligent optimization algorithm performs well in solving complex optimization problems in engineering. However, the intelligent optimization algorithm usually takes long execution time and large memory usage, which is not suitable for the engineering with limited hardware conditions.
Zhihao Yu, Jialu Du, Guangqiang Li
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An intensify Harris Hawks optimizer for numerical and engineering optimization problems

Applied Soft Computing, 2020
Abstract Recently developed Harris Hawks Optimization has virtuous behavior for finding optimum solution in search space. However, it easily get trapped into local search space for constrained engineering optimization problems. In order to accelerate the global search phase of existing Harris Hawks optimizer and to stuck it out of local search space,
Vikram Kumar Kamboj, Ayani Nandi, Ashutosh Bhadoria, Shivani Sehgal   +3 more
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Hierarchical Harris hawks optimization for epileptic seizure classification

Computers in Biology and Medicine, 2022
The intelligent recognition of electroencephalogram (EEG) signals is a valuable tool for epileptic seizure classification. Given that visual inspection of EEG signals is time-consuming, and that mutant signals dramatically increase the workload of neurologists, automatic epilepsy diagnosis systems are extremely helpful.
Zhenzhen Luo, Shan Jin, Zuoyong Li, Hui Huang 0009, Lei Xiao 0007, Huiling Chen 0001, Ali Asghar Heidari, Jiao Hu, Changzu Chen, Peiyu Chen, Zhongyi Hu 0001   +10 more
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Boosted binary Harris hawks optimizer and feature selection

Engineering with Computers, 2020
Feature selection is a required preprocess stage in most of the data mining tasks. This paper presents an improved Harris hawks optimization (HHO) to find high-quality solutions for global optimization and feature selection tasks. This method is an efficient optimizer inspired by the behaviors of Harris' hawks, which try to catch the rabbits.
Yanan Zhang, Renjing Liu, Xin Wang 0154, Huiling Chen 0001, Chengye Li   +4 more
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Improved Harris Hawks Optimization Algorithm

Concurrency and Computation: Practice and Experience
ABSTRACTThe Harris Hawks Optimization (HHO) algorithm is a nature‐inspired metaheuristic that mimics the cooperative hunting behavior of hawks. Despite its success in various optimization tasks, it suffers from several limitations, including low computational accuracy, a tendency to become trapped in local optima, and difficulty in balancing ...
Xiaopei Liu, Yong Zhang, Yanqin Li, Bai Yu, Qi Chen   +4 more
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An improved Harris Hawks Optimization algorithm for continuous and discrete optimization problems

Engineering Applications of Artificial Intelligence, 2022
Harris Hawks Optimization (HHO) is a population-based meta-heuristic optimization algorithm that has been used for the solution of test functions and real-world problems by many researchers. However, HHO has a premature convergence problem. The main motive of the novel approach in this paper is that the performance of an MHA could be improved by ...
Harun Gezici, Haydar Livatyali
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Chaotic Harris Hawks Optimization for Unconstrained Function Optimization

2020 16th International Computer Engineering Conference (ICENCO), 2020
Swarm-based techniques, a form of meta-heuristic techniques, are derived from the swarm system's social conduct in nature. A newly brought optimization algorithm is Harris Hawks Optimization (HHO) that is stimulated through looking conduct of Harris Hawks (agents) of finding food (optimal solution).
Abdelhameed Ibrahim, Hesham Arafat Ali, Marwa M. Eid, El-Sayed M. El-kenawy   +3 more
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Passive vehicle suspension system optimization using Harris Hawk Optimization algorithm

Mathematics and Computers in Simulation, 2022
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Mohamed Issa, Anas Samn
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Harris Hawks Optimizer

2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture, 2021
Jingfeng Rong, Di Wang
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Training Multi-Layer Perceptron Using Harris Hawks Optimization

2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), 2020
In this paper, Harris hawks optimization (HHO) algorithm has been proposed as an up-to-date meta-heuristic algorithm for training multi-layer perceptron (MLP). The performance of the HHO-based MLP trainer was tested by employing five standard data sets (XOR, Balloon, Iris, Breast Cancer and Heart). The results were compared with those obtained with the
Eker, Erdal, Kayri, Murat, Ekinci, Serdar, İzci, Davut   +3 more
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