Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (5)
  • Open Access


    A Deep Reinforcement Learning-Based Technique for Optimal Power Allocation in Multiple Access Communications

    Sepehr Soltani1, Ehsan Ghafourian2, Reza Salehi3, Diego Martín3,*, Milad Vahidi4

    Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 93-108, 2024, DOI:10.32604/iasc.2024.042693

    Abstract For many years, researchers have explored power allocation (PA) algorithms driven by models in wireless networks where multiple-user communications with interference are present. Nowadays, data-driven machine learning methods have become quite popular in analyzing wireless communication systems, which among them deep reinforcement learning (DRL) has a significant role in solving optimization issues under certain constraints. To this purpose, in this paper, we investigate the PA problem in a -user multiple access channels (MAC), where transmitters (e.g., mobile users) aim to send an independent message to a common receiver (e.g., base station) through wireless channels. To… More >

  • Open Access


    Adaptive Kernel Firefly Algorithm Based Feature Selection and Q-Learner Machine Learning Models in Cloud

    I. Mettildha Mary1,*, K. Karuppasamy2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2667-2685, 2023, DOI:10.32604/csse.2023.031114

    Abstract CC’s (Cloud Computing) networks are distributed and dynamic as signals appear/disappear or lose significance. MLTs (Machine learning Techniques) train datasets which sometime are inadequate in terms of sample for inferring information. A dynamic strategy, DevMLOps (Development Machine Learning Operations) used in automatic selections and tunings of MLTs result in significant performance differences. But, the scheme has many disadvantages including continuity in training, more samples and training time in feature selections and increased classification execution times. RFEs (Recursive Feature Eliminations) are computationally very expensive in its operations as it traverses through each feature without considering correlations More >

  • Open Access


    3D Path Optimisation of Unmanned Aerial Vehicles Using Q Learning-Controlled GWO-AOA

    K. Sreelakshmy1, Himanshu Gupta1, Om Prakash Verma1, Kapil Kumar2, Abdelhamied A. Ateya3, Naglaa F. Soliman4,*

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2483-2503, 2023, DOI:10.32604/csse.2023.032737

    Abstract Unmanned Aerial Vehicles (UAVs) or drones introduced for military applications are gaining popularity in several other fields as well such as security and surveillance, due to their ability to perform repetitive and tedious tasks in hazardous environments. Their increased demand created the requirement for enabling the UAVs to traverse independently through the Three Dimensional (3D) flight environment consisting of various obstacles which have been efficiently addressed by metaheuristics in past literature. However, not a single optimization algorithms can solve all kind of optimization problem effectively. Therefore, there is dire need to integrate metaheuristic for general More >

  • Open Access


    Q-Learning-Based Pesticide Contamination Prediction in Vegetables and Fruits

    Kandasamy Sellamuthu*, Vishnu Kumar Kaliappan

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 715-736, 2023, DOI:10.32604/csse.2023.029017

    Abstract Pesticides have become more necessary in modern agricultural production. However, these pesticides have an unforeseeable long-term impact on people's wellbeing as well as the ecosystem. Due to a shortage of basic pesticide exposure awareness, farmers typically utilize pesticides extremely close to harvesting. Pesticide residues within foods, particularly fruits as well as veggies, are a significant issue among farmers, merchants, and particularly consumers. The residual concentrations were far lower than these maximal allowable limits, with only a few surpassing the restrictions for such pesticides in food. There is an obligation to provide a warning about this… More >

  • Open Access


    Strategy Selection for Moving Target Defense in Incomplete Information Game

    Huan Zhang1, Kangfeng Zheng1, *, Xiujuan Wang2, Shoushan Luo1, Bin Wu1

    CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 763-786, 2020, DOI:10.32604/cmc.2020.06553

    Abstract As a core component of the network, web applications have become one of the preferred targets for attackers because the static configuration of web applications simplifies the exploitation of vulnerabilities by attackers. Although the moving target defense (MTD) has been proposed to increase the attack difficulty for the attackers, there is no solo approach can cope with different attacks; in addition, it is impossible to implement all these approaches simultaneously due to the resource limitation. Thus, the selection of an optimal defense strategy based on MTD has become the focus of research. In general, the… More >

Displaying 1-10 on page 1 of 5. Per Page