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  • Open Access

    ARTICLE

    Improved Attentive Recurrent Network for Applied Linguistics-Based Offensive Speech Detection

    Manar Ahmed Hamza1,*, Hala J. Alshahrani2, Khaled Tarmissi3, Ayman Yafoz4, Amira Sayed A. Aziz5, Mohammad Mahzari6, Abu Sarwar Zamani1, Ishfaq Yaseen1

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1691-1707, 2023, DOI:10.32604/csse.2023.034798

    Abstract Applied linguistics is one of the fields in the linguistics domain and deals with the practical applications of the language studies such as speech processing, language teaching, translation and speech therapy. The ever-growing Online Social Networks (OSNs) experience a vital issue to confront, i.e., hate speech. Amongst the OSN-oriented security problems, the usage of offensive language is the most important threat that is prevalently found across the Internet. Based on the group targeted, the offensive language varies in terms of adult content, hate speech, racism, cyberbullying, abuse, trolling and profanity. Amongst these, hate speech is the most intimidating form of… More >

  • Open Access

    REVIEW

    Research Progress of Aerodynamic Multi-Objective Optimization on High-Speed Train Nose Shape

    Zhiyuan Dai, Tian Li*, Weihua Zhang, Jiye Zhang

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1461-1489, 2023, DOI:10.32604/cmes.2023.028677

    Abstract The aerodynamic optimization design of high-speed trains (HSTs) is crucial for energy conservation, environmental preservation, operational safety, and speeding up. This study aims to review the current state and progress of the aerodynamic multi-objective optimization of HSTs. First, the study explores the impact of train nose shape parameters on aerodynamic performance. The parameterization methods involved in the aerodynamic multiobjective optimization of HSTs are summarized and classified as shape-based and disturbance-based parameterization methods. Meanwhile, the advantages and limitations of each parameterization method, as well as the applicable scope, are briefly discussed. In addition, the NSGA-II algorithm, particle swarm optimization algorithm, standard… More >

  • Open Access

    ARTICLE

    Hyperparameter Optimization for Capsule Network Based Modified Hybrid Rice Optimization Algorithm

    Zhiwei Ye1, Ziqian Fang1, Zhina Song1,*, Haigang Sui2, Chunyan Yan1, Wen Zhou1, Mingwei Wang1

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2019-2035, 2023, DOI:10.32604/iasc.2023.039949

    Abstract Hyperparameters play a vital impact in the performance of most machine learning algorithms. It is a challenge for traditional methods to configure hyperparameters of the capsule network to obtain high-performance manually. Some swarm intelligence or evolutionary computation algorithms have been effectively employed to seek optimal hyperparameters as a combinatorial optimization problem. However, these algorithms are prone to get trapped in the local optimal solution as random search strategies are adopted. The inspiration for the hybrid rice optimization (HRO) algorithm is from the breeding technology of three-line hybrid rice in China, which has the advantages of easy implementation, less parameters and… More >

  • Open Access

    ARTICLE

    QoS-Aware Cloud Service Optimization Algorithm in Cloud Manufacturing Environment

    Wenlong Ma1,2,*, Youhong Xu1, Jianwei Zheng2, Sadaqat ur Rehman3

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1499-1512, 2023, DOI:10.32604/iasc.2023.030484

    Abstract In a cloud manufacturing environment with abundant functionally equivalent cloud services, users naturally desire the highest-quality service(s). Thus, a comprehensive measurement of quality of service (QoS) is needed. Optimizing the plethora of cloud services has thus become a top priority. Cloud service optimization is negatively affected by untrusted QoS data, which are inevitably provided by some users. To resolve these problems, this paper proposes a QoS-aware cloud service optimization model and establishes QoS-information awareness and quantification mechanisms. Untrusted data are assessed by an information correction method. The weights discovered by the variable precision Rough Set, which mined the evaluation indicators… More >

  • Open Access

    ARTICLE

    STUDY ON WAX DEPOSITION RATE OPTIMIZATION ALGORITHM BASED ON LEVENBERG-MARQUARDT ALGORITHM AND GLOBAL OPTIMIZATION

    Rongge Xiaoa , Yue Zhub,*, Wenbo Jina , Zheng Daia , Shifang Lia , Fan Zhangc

    Frontiers in Heat and Mass Transfer, Vol.12, pp. 1-6, 2019, DOI:10.5098/hmt.12.28

    Abstract In order to accurately obtain the wax deposition rate model, according to the kinetic principle of wax deposition, several factors affecting the wax deposition rate were selected, and by a optimization software of First Optimization(1stOpt), The parameters of two typical wax deposition rate models are solved respectively based on optimization algorithm combined by Levenberg-Marquardt (L-M) algorithm and global optimization and the calculated data were compared. The results show that: compared with the model parameters obtained by least squares method, the model parameters obtained by this optimization algorithm can describe the variation of wax deposition rate more accurately. The maximum error… More >

  • Open Access

    ARTICLE

    Comparative Analysis for Evaluating Wind Energy Resources Using Intelligent Optimization Algorithms and Numerical Methods

    Musaed Alrashidi*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 491-513, 2023, DOI:10.32604/csse.2023.038628

    Abstract Statistical distributions are used to model wind speed, and the two-parameters Weibull distribution has proven its effectiveness at characterizing wind speed. Accurate estimation of Weibull parameters, the scale (c) and shape (k), is crucial in describing the actual wind speed data and evaluating the wind energy potential. Therefore, this study compares the most common conventional numerical (CN) estimation methods and the recent intelligent optimization algorithms (IOA) to show how precise estimation of c and k affects the wind energy resource assessments. In addition, this study conducts technical and economic feasibility studies for five sites in the northern part of Saudi… More >

  • Open Access

    ARTICLE

    Safety Assessment of Liquid Launch Vehicle Structures Based on Interpretable Belief Rule Base

    Gang Xiang1,2, Xiaoyu Cheng3, Wei He3,4,*, Peng Han3

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 273-298, 2023, DOI:10.32604/csse.2023.037892

    Abstract A liquid launch vehicle is an important carrier in aviation, and its regular operation is essential to maintain space security. In the safety assessment of fluid launch vehicle body structure, it is necessary to ensure that the assessment model can learn self-response rules from various uncertain data and not differently to provide a traceable and interpretable assessment process. Therefore, a belief rule base with interpretability (BRB-i) assessment method of liquid launch vehicle structure safety status combines data and knowledge. Moreover, an innovative whale optimization algorithm with interpretable constraints is proposed. The experiments are carried out based on the liquid launch… More >

  • Open Access

    ARTICLE

    Modified Dwarf Mongoose Optimization Enabled Energy Aware Clustering Scheme for Cognitive Radio Wireless Sensor Networks

    Sami Saeed Binyamin1, Mahmoud Ragab2,*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 105-119, 2023, DOI:10.32604/csse.2023.037311

    Abstract Cognitive radio wireless sensor networks (CRWSN) can be defined as a promising technology for developing bandwidth-limited applications. CRWSN is widely utilized by future Internet of Things (IoT) applications. Since a promising technology, Cognitive Radio (CR) can be modelled to alleviate the spectrum scarcity issue. Generally, CRWSN has cognitive radio-enabled sensor nodes (SNs), which are energy limited. Hierarchical cluster-related techniques for overall network management can be suitable for the scalability and stability of the network. This paper focuses on designing the Modified Dwarf Mongoose Optimization Enabled Energy Aware Clustering (MDMO-EAC) Scheme for CRWSN. The MDMO-EAC technique mainly intends to group the… More >

  • Open Access

    ARTICLE

    Hybrid Chameleon and Honey Badger Optimization Algorithm for QoS-Based Cloud Service Composition Problem

    G. Manimala*, A. Chinnasamy

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 393-412, 2023, DOI:10.32604/csse.2023.037066

    Abstract Cloud computing facilitates the great potentiality of storing and managing remote access to services in terms of software as a service (SaaS). Several organizations have moved towards outsourcing over the cloud to reduce the burden on local resources. In this context, the metaheuristic optimization method is determined to be highly suitable for selecting appropriate services that comply with the requirements of the client’s requests, as the services stored over the cloud are too complex and scalable. To achieve better service composition, the parameters of Quality of Service (QoS) related to each service considered to be the best resource need to… More >

  • Open Access

    ARTICLE

    Adaptive Butterfly Optimization Algorithm (ABOA) Based Feature Selection and Deep Neural Network (DNN) for Detection of Distributed Denial-of-Service (DDoS) Attacks in Cloud

    S. Sureshkumar1,*, G .K. D. Prasanna Venkatesan2, R. Santhosh3

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1109-1123, 2023, DOI:10.32604/csse.2023.036267

    Abstract Cloud computing technology provides flexible, on-demand, and completely controlled computing resources and services are highly desirable. Despite this, with its distributed and dynamic nature and shortcomings in virtualization deployment, the cloud environment is exposed to a wide variety of cyber-attacks and security difficulties. The Intrusion Detection System (IDS) is a specialized security tool that network professionals use for the safety and security of the networks against attacks launched from various sources. DDoS attacks are becoming more frequent and powerful, and their attack pathways are continually changing, which requiring the development of new detection methods. Here the purpose of the study… More >

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