Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (26)
  • Open Access

    ARTICLE

    Hybridizing Artificial Bee Colony with Bat Algorithm for Web Service Composition

    Tariq Ahamed Ahanger1,*, Fadl Dahan2,3, Usman Tariq1

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2429-2445, 2023, DOI:10.32604/csse.2023.037692

    Abstract In the Internet of Things (IoT), the users have complex needs, and the Web Service Composition (WSC) was introduced to address these needs. The WSC’s main objective is to search for the optimal combination of web services in response to the user needs and the level of Quality of Services (QoS) constraints. The challenge of this problem is the huge number of web services that achieve similar functionality with different levels of QoS constraints. In this paper, we introduce an extension of our previous works on the Artificial Bee Colony (ABC) and Bat Algorithm (BA).… More >

  • Open Access

    ARTICLE

    Optimal Machine Learning Driven Sentiment Analysis on COVID-19 Twitter Data

    Bahjat Fakieh1, Abdullah S. AL-Malaise AL-Ghamdi1,2,3, Farrukh Saleem1, Mahmoud Ragab2,4,5,6,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 81-97, 2023, DOI:10.32604/cmc.2023.033406

    Abstract The outbreak of the pandemic, caused by Coronavirus Disease 2019 (COVID-19), has affected the daily activities of people across the globe. During COVID-19 outbreak and the successive lockdowns, Twitter was heavily used and the number of tweets regarding COVID-19 increased tremendously. Several studies used Sentiment Analysis (SA) to analyze the emotions expressed through tweets upon COVID-19. Therefore, in current study, a new Artificial Bee Colony (ABC) with Machine Learning-driven SA (ABCML-SA) model is developed for conducting Sentiment Analysis of COVID-19 Twitter data. The prime focus of the presented ABCML-SA model is to recognize the sentiments More >

  • Open Access

    ARTICLE

    Selective Harmonics Elimination Technique for Artificial Bee Colony Implementation

    T. DeepikaVinothini1,*, R. Karthigaivel2, J. BarsanaBanu3

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2721-2740, 2023, DOI:10.32604/csse.2023.028662

    Abstract In this research, an Artificial Bee Colony (ABC) algorithm based Selective Harmonics Elimination (SHE) technique is used as a pulse generator in a reduced switch fifteen level inverter that receives input from a PV system. Pulse width modulation based on Selective Harmonics Elimination is mostly used to suppress lower-order harmonics. A high gain DC-DC-SEPIC converter keeps the photovoltaic (PV) panel’s output voltage constant. The Grey Wolf Optimization (GWO) filter removes far more Photovoltaic panel energy from the sunlight frame. To eliminate voltage harmonics, this unique inverter architecture employs a multi-carrier duty cycle, a high-frequency modulation More >

  • Open Access

    ARTICLE

    Cluster Head Selection and Multipath Routing Based Energy Efficient Wireless Sensor Network

    T. Shanmugapriya1,*, Dr. K. Kousalya2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 879-894, 2023, DOI:10.32604/iasc.2023.032074

    Abstract The Wireless Sensor Network (WSN) is a network of Sensor Nodes (SN) which adopt radio signals for communication amongst themselves. There is an increase in the prominence of WSN adaptability to emerging applications like the Internet of Things (IoT) and Cyber-Physical Systems (CPS). Data security, detection of faults, management of energy, collection and distribution of data, network protocol, network coverage, mobility of nodes, and network heterogeneity are some of the issues confronted by WSNs. There is not much published information on issues related to node mobility and management of energy at the time of aggregation… More >

  • Open Access

    ARTICLE

    Mobility Aware Zone-Based Routing in Vehicle Ad hoc Networks Using Hybrid Metaheuristic Algorithm

    C. Nandagopal1,*, P. Siva Kumar2, R. Rajalakshmi3, S. Anandamurugan4

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 113-126, 2023, DOI:10.32604/iasc.2023.031103

    Abstract Vehicle Ad hoc Networks (VANETs) have high mobility and a randomized connection structure, resulting in extremely dynamic behavior. Several challenges, such as frequent connection failures, sustainability, multi-hop data transfer, and data loss, affect the effectiveness of Transmission Control Protocols (TCP) on such wireless ad hoc networks. To avoid the problem, in this paper, mobility-aware zone-based routing in VANET is proposed. To achieve this concept, in this paper hybrid optimization algorithm is presented. The hybrid algorithm is a combination of Ant colony optimization (ACO) and artificial bee colony optimization (ABC). The proposed hybrid algorithm is designed for… More >

  • Open Access

    ARTICLE

    Artificial Bee Colony with Cuckoo Search for Solving Service Composition

    Fadl Dahan1,2,*, Abdulelah Alwabel3

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3385-3402, 2023, DOI:10.32604/iasc.2023.030651

    Abstract In recent years, cloud computing has provided a Software As A Service (SaaS) platform where the software can be reused and applied to fulfill complicated user demands according to specific Quality of Services (QoS) constraints. The user requirements are formulated as a workflow consisting of a set of tasks. However, many services may satisfy the functionality of each task; thus, searching for the composition of the optimal service while maximizing the QoS is formulated as an NP-hard problem. This work will introduce a hybrid Artificial Bee Colony (ABC) with a Cuckoo Search (CS) algorithm to… More >

  • Open Access

    ARTICLE

    Email Filtering Using Hybrid Feature Selection Model

    Adel Hamdan Mohammad1,* , Sami Smadi2, Tariq Alwada’n3

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 435-450, 2022, DOI:10.32604/cmes.2022.020088

    Abstract Undoubtedly, spam is a serious problem, and the number of spam emails is increased rapidly. Besides, the massive number of spam emails prompts the need for spam detection techniques. Several methods and algorithms are used for spam filtering. Also, some emergent spam detection techniques use machine learning methods and feature extraction. Some methods and algorithms have been introduced for spam detecting and filtering. This research proposes two models for spam detection and feature selection. The first model is evaluated with the email spam classification dataset, which is based on reducing the number of keywords to… More >

  • Open Access

    ARTICLE

    Resource Load Prediction of Internet of Vehicles Mobile Cloud Computing

    Wenbin Bi1, Fang Yu2, Ning Cao3,*, Russell Higgs4

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 165-180, 2022, DOI:10.32604/cmc.2022.027776

    Abstract Load-time series data in mobile cloud computing of Internet of Vehicles (IoV) usually have linear and nonlinear composite characteristics. In order to accurately describe the dynamic change trend of such loads, this study designs a load prediction method by using the resource scheduling model for mobile cloud computing of IoV. Firstly, a chaotic analysis algorithm is implemented to process the load-time series, while some learning samples of load prediction are constructed. Secondly, a support vector machine (SVM) is used to establish a load prediction model, and an improved artificial bee colony (IABC) function is designed… More >

  • Open Access

    ARTICLE

    Hybrid Sensorless Speed Control Technique for BLDC Motor Using ANFIS Automation

    S. S. Selva Pradeep*, M. Marsaline Beno

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1757-1770, 2022, DOI:10.32604/iasc.2022.023470

    Abstract The Brushless Direct Current (BLDC) motors have shown to be a cost-effective alternative to traditional motors. The smooth and efficient operation of the BLDC motor is dependent on speed regulation. This research proposes a sensorless intelligent speed control technique for BLDC using an Adaptive Network-based Fuzzy Inference Systems (ANFIS) based Artificial Bee Colony (ABC) algorithm. The motor’s back EMF is measured, and ANFIS is used to generate Hall signals. The ABC is then utilized to provide the pulses needed for the three-phase inverter, avoiding the requirement of logic gate circuits. The input DC voltage to… More >

  • Open Access

    ARTICLE

    A Novel Approach Based on Hybrid Algorithm for Energy Efficient Cluster Head Identification in Wireless Sensor Networks

    C. Ram Kumar1,*, K. Murali Krishna2, Mohammad Shabbir Alam3, K. Vigneshwaran4, Sridharan Kannan5, C. Bharatiraja6

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 259-273, 2022, DOI:10.32604/csse.2022.023477

    Abstract The Wireless Sensor Networks (WSN) is a self-organizing network with random deployment of wireless nodes that connects each other for effective monitoring and data transmission. The clustering technique employed to group the collection of nodes for data transmission and each node is assigned with a cluster head. The major concern with the identification of the cluster head is the consideration of energy consumption and hence this paper proposes an hybrid model which forms an energy efficient cluster head in the Wireless Sensor Network. The proposed model is a hybridization of Glowworm Swarm Optimization (GSO) and More >

Displaying 11-20 on page 2 of 26. Per Page