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Search Results (14)
  • Open Access

    ARTICLE

    Adaptive Cloud Intrusion Detection System Based on Pruned Exact Linear Time Technique

    Widad Elbakri1, Maheyzah Md. Siraj1,*, Bander Ali Saleh Al-rimy1, Sultan Noman Qasem2, Tawfik Al-Hadhrami3

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3725-3756, 2024, DOI:10.32604/cmc.2024.048105

    Abstract Cloud computing environments, characterized by dynamic scaling, distributed architectures, and complex workloads, are increasingly targeted by malicious actors. These threats encompass unauthorized access, data breaches, denial-of-service attacks, and evolving malware variants. Traditional security solutions often struggle with the dynamic nature of cloud environments, highlighting the need for robust Adaptive Cloud Intrusion Detection Systems (CIDS). Existing adaptive CIDS solutions, while offering improved detection capabilities, often face limitations such as reliance on approximations for change point detection, hindering their precision in identifying anomalies. This can lead to missed attacks or an abundance of false alarms, impacting overall… More >

  • Open Access

    ARTICLE

    An Optimized System of Random Forest Model by Global Harmony Search with Generalized Opposition-Based Learning for Forecasting TBM Advance Rate

    Yingui Qiu1, Shuai Huang1, Danial Jahed Armaghani2, Biswajeet Pradhan3, Annan Zhou4, Jian Zhou1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2873-2897, 2024, DOI:10.32604/cmes.2023.029938

    Abstract As massive underground projects have become popular in dense urban cities, a problem has arisen: which model predicts the best for Tunnel Boring Machine (TBM) performance in these tunneling projects? However, performance level of TBMs in complex geological conditions is still a great challenge for practitioners and researchers. On the other hand, a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction schedule. The performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine specifications. The previously-proposed intelligent techniques in this field… More >

  • Open Access

    ARTICLE

    Efficient Heuristic Replication Techniques for High Data Availability in Cloud

    H. L. Chandrakala1,*, R. Loganathan2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 3151-3164, 2023, DOI:10.32604/csse.2022.027873

    Abstract Most social networks allow connections amongst many people based on shared interests. Social networks have to offer shared data like videos, photos with minimum latency to the group, which could be challenging as the storage cost has to be minimized and hence entire data replication is not a solution. The replication of data across a network of read-intensive can potentially lead to increased savings in cost and energy and reduce the end-user’s response time. Though simple and adaptive replication strategies exist, the solution is non-deterministic; the replicas of the data need to be optimized to… More >

  • Open Access

    ARTICLE

    A Hybridized Artificial Neural Network for Automated Software Test Oracle

    K. Kamaraj1,*, B. Lanitha2, S. Karthic3, P. N. Senthil Prakash4, R. Mahaveerakannan5

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1837-1850, 2023, DOI:10.32604/csse.2023.029703

    Abstract Software testing is the methodology of analyzing the nature of software to test if it works as anticipated so as to boost its reliability and quality. These two characteristics are very critical in the software applications of present times. When testers want to perform scenario evaluations, test oracles are generally employed in the third phase. Upon test case execution and test outcome generation, it is essential to validate the results so as to establish the software behavior’s correctness. By choosing a feasible technique for the test case optimization and prioritization as along with an appropriate… More >

  • Open Access

    ARTICLE

    Generating of Test Data by Harmony Search Against Genetic Algorithms

    Ahmed S. Ghiduk1,2,*, Abdullah Alharbi1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 647-665, 2023, DOI:10.32604/iasc.2023.031865

    Abstract Many search-based algorithms have been successfully applied in several software engineering activities. Genetic algorithms (GAs) are the most used in the scientific domains by scholars to solve software testing problems. They imitate the theory of natural selection and evolution. The harmony search algorithm (HSA) is one of the most recent search algorithms in the last years. It imitates the behavior of a musician to find the best harmony. Scholars have estimated the similarities and the differences between genetic algorithms and the harmony search algorithm in diverse research domains. The test data generation process represents a… More >

  • Open Access

    ARTICLE

    Optimal Operation of Electric Vehicles and Distributed Generation Resources in Smart Grid Considering Load Management

    Zheng Wang*, Shangke Liu, Yanli Xiao, Ye Wan, Bin Bai

    Energy Engineering, Vol.119, No.6, pp. 2655-2679, 2022, DOI:10.32604/ee.2022.021843

    Abstract Technology advancement and the global tendency to use renewable energy in distributed generation units in the distribution network have been proposed as sources of energy supply. Despite the complexity of their protection, as well as the operation of distributed generation resources in the distribution network, factors such as improving reliability, increasing production capacity of the distribution network, stabilizing the voltage of the distribution network, reducing peak clipping losses, as well as economic and environmental considerations, have expanded the influence of distributed generation (DG) resources in the distribution network. The location of DG sources and their… More >

  • Open Access

    ARTICLE

    Modeling the Proposal of the Simultaneous Purchases and Sales of Electricity and Gas for the Energy Market in a Microgrid Using the Harmony Search Algorithm

    Zinan Zhou, Yirun Chen, Wensheng Dai*

    Energy Engineering, Vol.119, No.6, pp. 2681-2709, 2022, DOI:10.32604/ee.2022.021410

    Abstract The use of different energy carriers together, known as an energy hub, has been a hot topic of research in recent years amongst scientists and researchers. The term energy hub refers to the simultaneous operation of various infrastructures for energy generation and transfer, which has gained momentum in the form of microgrids (MGs). This paper introduces a new strategy for the optimal performance of an MG consisting of different energy carriers for each day. In a smart distribution network (DN), MGs can reduce their own costs in the previous-day market by bidding on sales and… More >

  • Open Access

    ARTICLE

    Implementing an Optimal Energy Management System for a Set of Microgrids Using the Harmony Search Algorithm

    Xiangjian Shi1,*, Teng Liu2, Wei Mu2, Jianfeng Zhao1

    Energy Engineering, Vol.119, No.5, pp. 1843-1860, 2022, DOI:10.32604/ee.2022.020787

    Abstract A microgrid (MG) refers to a set of loads, generation resources and energy storage systems acting as a controllable load or a generator to supply power and heating to a local area. The MG-generated power management is a central topic for MG design and operation. The existence of dispersed generation (DG) resources has faced MG management with new issues. Depending on the level of exchanges between an MG and the main grid, the MG operation states can be divided into independent or grid-connected ones. Energy management in MGs aims to supply power at the lowest… More >

  • Open Access

    ARTICLE

    Improved Harmony Search with Optimal Deep Learning Enabled Classification Model

    Mahmoud Ragab1,2,3,*, Adel A. Bahaddad4

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1783-1797, 2022, DOI:10.32604/cmc.2022.028055

    Abstract Due to drastic increase in the generation of data, it is tedious to examine and derive high level knowledge from the data. The rising trends of high dimension data gathering and problem representation necessitates feature selection process in several machine learning processes. The feature selection procedure establishes a generally encountered issue of global combinatorial optimization. The FS process can lessen the number of features by the removal of unwanted and repetitive data. In this aspect, this article introduces an improved harmony search based global optimization for feature selection with optimal deep learning (IHSFS-ODL) enabled classification… More >

  • Open Access

    ARTICLE

    Hybrid Renewable Energy System Using Cuckoo Firefly Optimization

    M. E. Shajini Sheeba1,*, P. Jagatheeswari2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1141-1156, 2022, DOI:10.32604/iasc.2022.024549

    Abstract With abundant and non-polluting benefits in nature, sources of renewable energy have reached vast concentrations. This paper first discusses the number of MPPT (Maximum Power Point Tracking) techniques utilized by wind and photovoltaic (PV) to create hybrid systems for generating wind-PV energy. This hybrid system complements each other day and night to enable continuous power output. Then, a new MPPT technique was proposed to extract maximum power using a newly developed hybrid optimization algorithm, namely the Cukoo Fire Fly method (CFF). The CFF algorithm is derived from the integration of the cuckoo search (CS) algorithm More >

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