Ting Cai¹, Chun Ye¹, Zhiwei Ye^1,*, Ziyuan Chen¹, Mengqing Mei¹, Haichao Zhang¹, Wanfang Bai², Peng Zhang³

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1157-1175, 2024, DOI:10.32604/cmc.2024.055080 - 15 October 2024

Abstract The world produces vast quantities of high-dimensional multi-semantic data. However, extracting valuable information from such a large amount of high-dimensional and multi-label data is undoubtedly arduous and challenging. Feature selection aims to mitigate the adverse impacts of high dimensionality in multi-label data by eliminating redundant and irrelevant features. The ant colony optimization algorithm has demonstrated encouraging outcomes in multi-label feature selection, because of its simplicity, efficiency, and similarity to reinforcement learning. Nevertheless, existing methods do not consider crucial correlation information, such as dynamic redundancy and label correlation. To tackle these concerns, the paper proposes a More >

Varada Rajkumar Kukkala¹, Surapaneni Phani Praveen², Naga Satya Koti Mani Kumar Tirumanadham³, Parvathaneni Naga Srinivasu^4,5,*

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1085-1112, 2024, DOI:10.32604/csse.2024.053603 - 13 September 2024

Abstract This paper investigates the application of machine learning to develop a response model to cardiovascular problems and the use of AdaBoost which incorporates an application of Outlier Detection methodologies namely; Z-Score incorporated with Grey Wolf Optimization (GWO) as well as Interquartile Range (IQR) coupled with Ant Colony Optimization (ACO). Using a performance index, it is shown that when compared with the Z-Score and GWO with AdaBoost, the IQR and ACO, with AdaBoost are not very accurate (89.0% vs. 86.0%) and less discriminative (Area Under the Curve (AUC) score of 93.0% vs. 91.0%). The Z-Score and GWO… More >

V. G. Saranya^*, S. Karthik

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 127-150, 2024, DOI:10.32604/cmes.2024.053825 - 20 August 2024

Abstract Wireless Sensor Networks (WSNs) are a collection of sensor nodes distributed in space and connected through wireless communication. The sensor nodes gather and store data about the real world around them. However, the nodes that are dependent on batteries will ultimately suffer an energy loss with time, which affects the lifetime of the network. This research proposes to achieve its primary goal by reducing energy consumption and increasing the network’s lifetime and stability. The present technique employs the hybrid Mayfly Optimization Algorithm-Enhanced Ant Colony Optimization (MFOA-EACO), where the Mayfly Optimization Algorithm (MFOA) is used to… More >

Abdulaziz Attaallah¹, Khalil al-Sulbi², Areej Alasiry³, Mehrez Marzougui³, Mohd Waris Khan^4,*, Mohd Faizan⁴, Alka Agrawal⁵, Dhirendra Pandey⁵

Computer Systems Science and Engineering, Vol.47, No.3, pp. 3165-3195, 2023, DOI:10.32604/csse.2023.040259 - 09 November 2023

Abstract Security testing is a critical concern for organizations worldwide due to the potential financial setbacks and damage to reputation caused by insecure software systems. One of the challenges in software security testing is test case prioritization, which aims to reduce redundancy in fault occurrences when executing test suites. By effectively applying test case prioritization, both the time and cost required for developing secure software can be reduced. This paper proposes a test case prioritization technique based on the Ant Colony Optimization (ACO) algorithm, a metaheuristic approach. The performance of the ACO-based technique is evaluated using More >

Abida Sharif¹, Imran Sharif¹, Muhammad Asim Saleem², Muhammad Attique Khan³, Majed Alhaisoni⁴, Marriam Nawaz^5,6, Abdullah Alqahtani⁷, Ye Jin Kim⁸, Byoungchol Chang^9,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5379-5393, 2023, DOI:10.32604/cmc.2023.034413 - 29 April 2023

Abstract The Internet of Vehicles (IoV) is a networking paradigm related to the intercommunication of vehicles using a network. In a dynamic network, one of the key challenges in IoV is traffic management under increasing vehicles to avoid congestion. Therefore, optimal path selection to route traffic between the origin and destination is vital. This research proposed a realistic strategy to reduce traffic management service response time by enabling real-time content distribution in IoV systems using heterogeneous network access. Firstly, this work proposed a novel use of the Ant Colony Optimization (ACO) algorithm and formulated the path More >

Sana Abbas¹, Faraha Ashraf¹, Fahd Jarad^2,3,*, Muhammad Shoaib Sardar¹, Imran Siddique⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1917-1930, 2023, DOI:10.32604/cmes.2023.024700 - 06 February 2023

Abstract This article presents an optimized approach of mathematical techniques in the medical domain by manoeuvring the phenomenon of ant colony optimization algorithm (also known as ACO). A complete graph of blood banks and a path that covers all the blood banks without repeating any link is required by applying the Travelling Salesman Problem (often TSP). The wide use promises to accelerate and offers the opportunity to cultivate health care, particularly in remote or unmerited environments by shrinking lab testing reversal times, empowering just-in-time lifesaving medical supply. More >

Tzu-Chia Chen¹, Ngakan Ketut Acwin Dwijendra², I. Wayan Parwata³, Agata Iwan Candra⁴, Elsayed M. Tag El Din^5,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1305-1316, 2023, DOI:10.32604/cmc.2023.033274 - 06 February 2023

Abstract Because solar energy is among the renewable energies, it has traditionally been used to provide lighting in buildings. When solar energy is effectively utilized during the day, the environment is not only more comfortable for users, but it also utilizes energy more efficiently for both heating and cooling purposes. Because of this, increasing the building’s energy efficiency requires first controlling the amount of light that enters the space. Considering that the only parts of the building that come into direct contact with the sun are the windows, it is essential to make use of louvers… More >

ZEKUN XIN^1,#, YUDAN MA^2,#, WEIQIANG SONG³, HAO GAO³, LIJUN DONG³, BAO ZHANG^1,*, ZHILONG REN^3,*

BIOCELL, Vol.47, No.3, pp. 555-567, 2023, DOI:10.32604/biocell.2023.026254 - 03 January 2023

Abstract Background: Recently, researchers have been attracted in identifying the crucial genes related to cancer, which plays important role in cancer diagnosis and treatment. However, in performing the cancer molecular subtype classification task from cancer gene expression data, it is challenging to obtain those significant genes due to the high dimensionality and high noise of data. Moreover, the existing methods always suffer from some issues such as premature convergence. Methods: To address those problems, we propose a new ant colony optimization (ACO) algorithm called DACO to classify the cancer gene expression datasets, identifying the essential genes of… More >

Chuan Wang^1,*, Ruoyu Zhu², Yi Jiang³, Weili Liu⁴, Sang-Woon Jeon⁵, Lin Sun², Hua Wang⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1209-1228, 2023, DOI:10.32604/cmes.2022.022807 - 27 October 2022

Abstract The dynamic traveling salesman problem (DTSP) is significant in logistics distribution in real-world applications in smart cities, but it is uncertain and difficult to solve. This paper proposes a scheme library-based ant colony optimization (ACO) with a two-optimization (2-opt) strategy to solve the DTSP efficiently. The work is novel and contributes to three aspects: problem model, optimization framework, and algorithm design. Firstly, in the problem model, traditional DTSP models often consider the change of travel distance between two nodes over time, while this paper focuses on a special DTSP model in that the node locations… More >

S. Vanitha^1,*, P. Balasubramanie²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 849-864, 2023, DOI:10.32604/iasc.2023.032324 - 29 September 2022

Abstract Internet of things (IOT) possess cultural, commercial and social effect in life in the future. The nodes which are participating in IOT network are basically attracted by the cyber-attack targets. Attack and identification of anomalies in IoT infrastructure is a growing problem in the IoT domain. Machine Learning Based Ensemble Intrusion Detection (MLEID) method is applied in order to resolve the drawback by minimizing malicious actions in related botnet attacks on Message Queue Telemetry Transport (MQTT) and Hyper-Text Transfer Protocol (HTTP) protocols. The proposed work has two significant contributions which are a selection of features… More >