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  • Open Access

    ARTICLE

    Intelligent Deer Hunting Optimization Based Grid Scheduling Scheme

    Mesfer Al Duhayyim1, Majdy M. Eltahir2, Imène Issaoui3, Fahd N. Al-Wesabi2,4, Anwer Mustafa Hilal5, Fuad Ali Mohammed Al-Yarimi2, Manar Ahmed Hamza5,*, Abu Sarwar Zamani5

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 181-195, 2022, DOI:10.32604/cmc.2022.024206 - 24 February 2022

    Abstract The grid environment is a dynamic, heterogeneous, and changeable computing system that distributes various services amongst different clients. To attain the benefits of collaborative resource sharing in Grid computing, a novel and proficient grid resource management system (RMS) is essential. Therefore, detection of an appropriate resource for the presented task is a difficult task. Several scientists have presented algorithms for mapping tasks to the resource. Few of them focus on fault tolerance, user fulfillment, and load balancing. With this motivation, this study designs an intelligent grid scheduling scheme using deer hunting optimization algorithm (DHOA), called More >

  • Open Access

    ARTICLE

    Hyperparameter Tuned Bidirectional Gated Recurrent Neural Network for Weather Forecasting

    S. Manikandan1,*, B. Nagaraj2

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 761-775, 2022, DOI:10.32604/iasc.2022.023398 - 08 February 2022

    Abstract Weather forecasting is primarily related to the prediction of weather conditions that becomes highly important in diverse applications like drought discovery, severe weather forecast, climate monitoring, agriculture, aviation, telecommunication, etc. Data-driven computer modelling with Artificial Neural Networks (ANN) can be used to solve non-linear problems. Presently, Deep Learning (DL) based weather forecasting models can be designed to accomplish reasonable predictive performance. In this aspect, this study presents a Hyper Parameter Tuned Bidirectional Gated Recurrent Neural Network (HPT-BiGRNN) technique for weather forecasting. The HPT-BiGRNN technique aims to utilize the past weather data for training the BiGRNN… More >

  • Open Access

    ARTICLE

    Optimized Deep Learning Model for Colorectal Cancer Detection and Classification Model

    Mahmoud Ragab1,2,3,*, Khalid Eljaaly4, Maha Farouk S. Sabir5, Ehab Bahaudien Ashary6, S. M. Abo-Dahab7,8, E. M. Khalil3,9

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5751-5764, 2022, DOI:10.32604/cmc.2022.024658 - 14 January 2022

    Abstract The recent developments in biological and information technologies have resulted in the generation of massive quantities of data it speeds up the process of knowledge discovery from biological systems. Due to the advancements of medical imaging in healthcare decision making, significant attention has been paid by the computer vision and deep learning (DL) models. At the same time, the detection and classification of colorectal cancer (CC) become essential to reduce the severity of the disease at an earlier stage. The existing methods are commonly based on the combination of textual features to examine the classifier… More >

  • Open Access

    ARTICLE

    Metaheuristic Based Data Gathering Scheme for Clustered UAVs in 6G Communication Network

    Ahmed S. Almasoud1, Siwar Ben Haj Hassine2, Nadhem NEMRI2, Fahd N. Al-Wesabi2,3, Manar Ahmed Hamza4,*, Anwer Mustafa Hilal4, Abdelwahed Motwakel4, Mesfer Al Duhayyim5

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5311-5325, 2022, DOI:10.32604/cmc.2022.024500 - 14 January 2022

    Abstract The sixth-generation (6G) wireless communication networks are anticipated in integrating aerial, terrestrial, and maritime communication into a robust system to accomplish trustworthy, quick, and low latency needs. It enables to achieve maximum throughput and delay for several applications. Besides, the evolution of 6G leads to the design of unmanned aerial vehicles (UAVs) in providing inexpensive and effective solutions in various application areas such as healthcare, environment monitoring, and so on. In the UAV network, effective data collection with restricted energy capacity poses a major issue to achieving high quality network communication. It can be addressed… More >

  • Open Access

    ARTICLE

    Fusion Based Tongue Color Image Analysis Model for Biomedical Applications

    Esam A. AlQaralleh1, Halah Nassif2, Bassam A. Y. Alqaralleh2,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5477-5490, 2022, DOI:10.32604/cmc.2022.024364 - 14 January 2022

    Abstract Tongue diagnosis is a novel and non-invasive approach commonly employed to carry out the supplementary diagnosis over the globe. Recently, several deep learning (DL) based tongue color image analysis models have existed in the literature for the effective detection of diseases. This paper presents a fusion of handcrafted with deep features based tongue color image analysis (FHDF-TCIA) technique to biomedical applications. The proposed FDHF-TCIA technique aims to investigate the tongue images using fusion model, and thereby determines the existence of disease. Primarily, the FHDF-TCIA technique comprises Gaussian filtering based preprocessing to eradicate the noise. The More >

  • Open Access

    ARTICLE

    Metaheuristic Optimization Algorithm for Signals Classification of Electroencephalography Channels

    Marwa M. Eid1,*, Fawaz Alassery2, Abdelhameed Ibrahim3, Mohamed Saber4

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4627-4641, 2022, DOI:10.32604/cmc.2022.024043 - 14 January 2022

    Abstract Digital signal processing of electroencephalography (EEG) data is now widely utilized in various applications, including motor imagery classification, seizure detection and prediction, emotion classification, mental task classification, drug impact identification and sleep state classification. With the increasing number of recorded EEG channels, it has become clear that effective channel selection algorithms are required for various applications. Guided Whale Optimization Method (Guided WOA), a suggested feature selection algorithm based on Stochastic Fractal Search (SFS) technique, evaluates the chosen subset of channels. This may be used to select the optimum EEG channels for use in Brain-Computer Interfaces More >

  • Open Access

    ARTICLE

    Binary Fruit Fly Swarm Algorithms for the Set Covering Problem

    Broderick Crawford1,*, Ricardo Soto1, Hanns de la Fuente Mella1, Claudio Elortegui1, Wenceslao Palma1, Claudio Torres-Rojas1, Claudia Vasconcellos-Gaete2, Marcelo Becerra1, Javier Peña1, Sanjay Misra3

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4295-4318, 2022, DOI:10.32604/cmc.2022.023068 - 14 January 2022

    Abstract Currently, the industry is experiencing an exponential increase in dealing with binary-based combinatorial problems. In this sense, metaheuristics have been a common trend in the field in order to design approaches to solve them successfully. Thus, a well-known strategy consists in the use of algorithms based on discrete swarms transformed to perform in binary environments. Following the No Free Lunch theorem, we are interested in testing the performance of the Fruit Fly Algorithm, this is a bio-inspired metaheuristic for deducing global optimization in continuous spaces, based on the foraging behavior of the fruit fly, which… More >

  • Open Access

    ARTICLE

    Metaheuristic Based Resource Scheduling Technique for Distributed Robotic Control Systems

    P. Anandraj1,*, S. Ramabalan2

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 795-811, 2022, DOI:10.32604/csse.2022.022107 - 04 January 2022

    Abstract The design of controllers for robots is a complex system that is to be dealt with several tasks in real time for enabling the robots to function independently. The distributed robotic control system can be used in real time for resolving various challenges such as localization, motion controlling, mapping, route planning, etc. The distributed robotic control system can manage different kinds of heterogenous devices. Designing a distributed robotic control system is a challenging process as it needs to operate effectually under different hardware configurations and varying computational requirements. For instance, scheduling of resources (such as… More >

  • Open Access

    ARTICLE

    Bacterial Foraging Based Algorithm Front-end to Solve Global Optimization Problems

    Betania Hernández-Ocaña, Adrian García-López, José Hernández-Torruco, Oscar Chávez-Bosquez*

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1797-1813, 2022, DOI:10.32604/iasc.2022.023570 - 09 December 2021

    Abstract The Bacterial Foraging Algorithm (BFOA) is a well-known swarm collective intelligence algorithm used to solve a variety of constraint optimization problems with wide success. Despite its universality, implementing the BFOA may be complex due to the calibration of multiple parameters. Moreover, the Two-Swim Modified Bacterial Foraging Optimization Algorithm (TS-MBFOA) is a state-of-the-art modification of the BFOA which may lead to solutions close to the optimal but with more parameters than the original BFOA. That is why in this paper we present the design using the Unified Modeling Language (UML) and the implementation in the MATLAB… More >

  • Open Access

    ARTICLE

    Design of QoS Aware Routing Protocol for IoT Assisted Clustered WSN

    Ashit Kumar Dutta1, S. Srinivasan2, Bobbili Prasada Rao3, B. Hemalatha4, Irina V. Pustokhina5, Denis A. Pustokhin6, Gyanendra Prasad Joshi7,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3785-3801, 2022, DOI:10.32604/cmc.2022.023657 - 07 December 2021

    Abstract In current days, the domain of Internet of Things (IoT) and Wireless Sensor Networks (WSN) are combined for enhancing the sensor related data transmission in the forthcoming networking applications. Clustering and routing techniques are treated as the effective methods highly used to attain reduced energy consumption and lengthen the lifetime of the WSN assisted IoT networks. In this view, this paper presents an Ensemble of Metaheuristic Optimization based QoS aware Clustering with Multihop Routing (EMO-QoSCMR) Protocol for IoT assisted WSN. The proposed EMO-QoSCMR protocol aims to achieve QoS parameters such as energy, throughput, delay, and… More >

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