Article
Computer Science, Theory & Methods
Joshua Peake, Martyn Amos, Nicholas Costen, Giovanni Masala, Huw Lloyd
Summary: This paper presents an improved algorithm for the Virtual Machine Placement (VMP) problem, which significantly improves the solution speed by utilizing parallelization techniques and modern processor technologies. The algorithm achieves solution qualities comparable to or even superior to other nature-inspired methods.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Dickson Odhiambo Owuor, Thomas Runkler, Anne Laurent, Joseph Onderi Orero, Edmond Odhiambo Menya
Summary: Gradual pattern extraction is a field in Knowledge Discovery in Databases that aims to map correlations between attributes of a data set as gradual dependencies. In this study, three population-based optimization techniques are investigated to improve the efficiency of mining gradual patterns. The results show that ant colony optimization technique outperforms genetic algorithm and particle swarm optimization in the task of gradual pattern mining.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2021)
Article
Computer Science, Artificial Intelligence
Xinsen Zhou, Wenyong Gui, Ali Asghar Heidari, Zhennao Cai, Guoxi Liang, Huiling Chen
Summary: Continuous ant colony optimization algorithm incorporates a random following strategy to enhance global optimization performance and effectively handle high-dimensional feature selection problems. The algorithm performs competitively with other state-of-the-art algorithms in benchmark tests and outperforms well-known classification methods on high-dimensional datasets.
APPLIED SOFT COMPUTING
(2023)
Article
Biology
Ailiang Qi, Dong Zhao, Fanhua Yu, Ali Asghar Heidari, Zongda Wu, Zhennao Cai, Fayadh Alenezi, Romany F. Mansour, Huiling Chen, Mayun Chen
Summary: This paper focuses on the study of COVID-19 X-ray image segmentation technology. A new multilevel image segmentation method based on the swarm intelligence algorithm is proposed, along with a designed image segmentation model. Experimental results show that the proposed model achieves more stable and superior segmentation results at different threshold levels.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biology
Lei Liu, Dong Zhao, Fanhua Yu, Ali Asghar Heidari, Chengye Li, Jinsheng Ouyang, Huiling Chen, Majdi Mafarja, Hamza Turabieh, Jingye Pan
Summary: This study introduces a multilevel COVID-19 X-ray image segmentation method based on ant colony optimization. By improving the algorithm, it effectively enhances the diagnostic level.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Computer Science, Artificial Intelligence
Abdelrahman Elsaid, Karl Ricanek, Zimeng Lyu, Alexander Ororbia, Travis Desell
Summary: Continuous Ant-based Topology Search (CANTS) is a novel nature-inspired neural architecture search algorithm based on ant colony optimization. It utilizes a continuous search space to automate the design of artificial neural networks, removing the limitation of predetermined structure sizes. By adding an extra dimension for neural synaptic weights, CANTS can optimize both architecture and weights, significantly reducing optimization time while maintaining competitive performance.
APPLIED SOFT COMPUTING
(2023)
Article
Biology
Song Yang, Lejing Lou, Wangjia Wang, Jie Li, Xiao Jin, Shijia Wang, Jihao Cai, Fangjun Kuang, Lei Liu, Myriam Hadjouni, Hela Elmannai, Chang Cai
Summary: This paper proposes a new algorithm called SCACO, which combines slime mould foraging behavior and collaborative hunting to improve the convergence accuracy and solution quality of ACOR. It also optimizes the ability of ACO to jump out of local optima using an adaptive collaborative hunting strategy. The performance of SCACO is compared with nine basic algorithms and nine variants, demonstrating its effectiveness in classification prediction for the diagnosis of tuberculous pleural effusion.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Computer Science, Interdisciplinary Applications
Yunlou Qian, Jiaqing Tu, Gang Luo, Ce Sha, Ali Asghar Heidari, Huiling Chen
Summary: This paper investigates the application of remote sensing images in urban surface morphology and geographic conditions, using the multi-threshold image segmentation method for image segmentation research. The performance of the original algorithm is enhanced by introducing salp foraging behavior. The experimental results demonstrate the advantages of SSACO in remote sensing image segmentation.
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING
(2023)
Article
Geosciences, Multidisciplinary
Chuanqi Li, Jian Zhou, Manoj Khandelwal, Xiliang Zhang, Masoud Monjezi, Yingui Qiu
Summary: Backbreak is a serious issue in open-pit mines, impacting the economic benefits and safety. This study proposes six different swarm intelligence optimization algorithms to predict backbreak, and the results show that combining swarm intelligence optimization algorithms with extreme learning machine techniques is effective for backbreak prediction.
NATURAL RESOURCES RESEARCH
(2022)
Article
Mathematics, Applied
Lamiaa M. El Bakrawy, Mehmet Akif Cifci, Samina Kausar, Sadiq Hussain, Md Akhtarul Islam, Bilal Alatas, Abeer S. Desuky
Summary: This study proposes a modified antlion optimization (MALO) algorithm to improve the primary antlion optimization algorithm (ALO) for the task of instance reduction. The results show that the MALO algorithm outperforms the basic ALO algorithm and other comparative algorithms in terms of convergence rate and performance measures like Accuracy, Balanced Accuracy (BACC), Geometric mean (G-mean), and Area Under the Curve (AUC). The MALO algorithm offers a potential solution to the problem of local optima stagnation and slow convergence speed.
Article
Engineering, Electrical & Electronic
Quan Xiao, Qing Ling, Tianyi Chen
Summary: This paper proposes a novel gradient estimation technique called LAZO for zeroth-order (ZO) methods. By adaptively reusing old queries, LAZO constructs low-variance gradient estimates, reducing the query complexity and achieving performance improvement in regret and query complexity relative to existing ZO methods.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2023)
Article
Computer Science, Artificial Intelligence
Sanchari Deb, Xiao-Zhi Gao
Summary: Transportation electrification is seen as a viable solution to global warming, air pollution, and energy crisis, but the optimal placement of charging infrastructure for Electric Vehicles presents a complex problem involving multiple design variables, objective functions, and constraints.
COMPLEX & INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Yuan Sun, Sheng Wang, Yunzhuang Shen, Xiaodong Li, Andreas T. Ernst, Michael Kirley
Summary: This paper introduces an enhanced meta-heuristic algorithm (ML-ACO) that combines machine learning and ant colony optimization to solve combinatorial optimization problems. The algorithm first trains a machine learning model using small problem instances with known optimal solutions, and then uses the model to predict the probability of an edge belonging to the optimal route. The predicted probabilities are then incorporated into the ant colony optimization algorithm to improve solution performance. The experimental results demonstrate the effectiveness of this approach for various optimization problems.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Mathematics
Ibrahim Al-Shourbaji, Na Helian, Yi Sun, Samah Alshathri, Mohamed Abd Elaziz
Summary: This paper discusses the importance of feature selection in the telecommunications industry for machine learning models. It introduces a new approach that combines ant colony optimization and reptile search algorithm, and evaluates its performance in customer churn prediction.
Article
Biology
Xixi He, Huajun Ye, Rui Zhao, Mengmeng Lu, Qiwen Chen, Lishimeng Bao, Tianmin Lv, Qiang Li, Fang Wu
Summary: Changes in human lifestyles have led to a dramatic increase in the incidence of Crohn's disease worldwide. Predicting the activity and remission of Crohn's disease has become an urgent research problem. In this paper, a wrapper feature selection classification model called bIACOR-KELM-FS was proposed, which combines the improved ant colony optimization algorithm and the kernel extreme learning machine. The model showed a high prediction accuracy of 98.98% for predicting the activity and remission of Crohn's disease, and the analysis of important attributes improved the interpretability of the model and provided a reference for the diagnosis of Crohn's disease.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Computer Science, Artificial Intelligence
Ayah M. Helal, Ashraf M. Abdelbar
Editorial Material
Law
Niko Tsakalakis, Sophie Stalla-Bourdillon, Laura Carmichael, Trung Dong Huynh, Luc Moreau, Ayah Helal
Summary: The legal debate around automated decision-making has mainly focused on the 'right to explanation' in the GDPR, while the emergence of XAI has introduced taxonomies for explaining AI systems. However, researchers have warned that transparency of algorithms alone is not sufficient, and better tools are needed for evaluating socio-technical systems. The PLEAD project suggests that explanations can aid in compliance strategies beyond GDPR requirements, and computable explanations can facilitate monitoring and auditing, benefiting both data subjects and controllers.
COMPUTER LAW & SECURITY REVIEW
(2021)
Article
Computer Science, Artificial Intelligence
Ayah Helal, Fernando E. B. Otero
Summary: This paper presents a new ACO-based algorithm for data stream classification called sAnt-Miner. By using a hybrid pheromone model, sAnt-Miner efficiently handles mixed-type attributes and reduces computational time, while maintaining high predictive accuracy.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Ayah Helal, James Brookhouse, Fernando E. B. Otero
2018 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
Ayah M. Helal, Enas Jawdat, Islam Elnabarawy, Ashraf M. Abdelbar, Donald C. Wunsch
2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI)
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Ayah Helal, Fernando E. B. Otero
PROCEEDINGS OF THE 2017 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'17)
(2017)
Proceedings Paper
Computer Science, Theory & Methods
Ayah Helal, Fernando E. B. Otero
GECCO'16: PROCEEDINGS OF THE 2016 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE
(2016)
Proceedings Paper
Computer Science, Artificial Intelligence
Ayah Helal, Enas Jawdat, Ashraf M. Abdelbar
2015 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
(2015)
Proceedings Paper
Automation & Control Systems
Ayah Helal, Florin Balasa
2015 20TH INTERNATIONAL CONFERENCE ON CONTROL SYSTEMS AND COMPUTER SCIENCE
(2015)