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    Wyświetlanie 1-4 z 4
    Tytuł:
    Optimal LQR controller in CSC based STATCOM using GA and PSO
    Autorzy:
    Gupta, S.
    Tripathi, R. K.
    Powiązania:
    https://bibliotekanauki.pl/articles/140927.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    CSC
    FACTS
    AI techniques
    LQR
    STATCOM
    Opis:
    The static synchronous compensator (STATCOM) is the multipurpose FACTS device with the multiple input and multiple output system for the enhancement of its dynamic performance in power system. Based on artificial intelligence (AI) optimization technique, a novel controller is proposed for CSC based STATCOM. In this paper, the CSC based STATCOM is controlled by the LQR. But the best constant values for LQR controller's parameters are obtained laboriously through trial and error method, although time consuming. So the goal of this paper is to investigate the ability of AI techniques such as genetic algorithm (GA) and particle swarm optimization (PSO) methods to search the best values of LQR controller's parameters in a very short time with the desired criterion for the test system. Performances of the GA, PSO & ABC based LQR controllers are also compared. Applicability of the proposed scheme is demonstrated through simulation in MATLAB and the simulation results are shown an improvement in the input-output response of CSC-STATCOM.
    Źródło:
    Archives of Electrical Engineering; 2014, 63, 3; 469-487
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Machine learning and artificial intelligence techniques for detecting driver drowsiness
    Autorzy:
    Prathap, Boppuru Rudra
    Kumar, Kukatlapalli Pradeep
    Hussain, Javid
    Chowdary, Cherukuri Ravindranath
    Powiązania:
    https://bibliotekanauki.pl/articles/27314194.pdf
    Data publikacji:
    2022
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    artificial intelligence
    machine learning
    drowsiness detection
    image processing
    convolutional neural networks
    AI visuals
    Opis:
    The number of automobiles on the road grows in lockstep with the advancement of vehicle manufacturing. Road accidents appear to be on the rise, owing to this growing proliferation of vehicles. Accidents frequently occur in our daily lives, and are the top ten causes of mortality from injuries globally. It is now an important component of the worldwide public health burden. Every year, an estimated 1.2 million people are killed in car accidents. Driver drowsiness and weariness are major contributors to traffic accidents this study relies on computer software and photographs, as well as a Convolutional Neural Network (CNN), to assess whether a motorist is tired. The Driver Drowsiness System is built on the MultiLayer Feed-Forward Network concept CNN was created using around 7,000 photos of eyes in both sleepiness and non-drowsiness phases with various face layouts. These photos were divided into two datasets: training (80% of the images) and testing (20% of the images). For training purposes, the pictures in the training dataset are fed into the network. To decrease information loss as much as feasible, backpropagation techniques and optimizers are applied. We developed an algorithm to calculate ROI as well as track and evaluate motor and visual impacts.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2022, 16, 2; 64--73
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Artificial Intelligence for Cybersecurity: Offensive Tactics, Mitigation Techniques and Future Directions
    Autorzy:
    Adi, Erwin
    Baig, Zubair
    Zeadally, Sherali
    Powiązania:
    https://bibliotekanauki.pl/articles/27272018.pdf
    Data publikacji:
    2022
    Wydawca:
    NASK - National Research Institute
    Tematy:
    artificial intelligence
    AI
    cyber infrastructures
    data analysis
    supply chain
    sztuczna inteligencja
    cybernetyczne infrastruktury
    analiza danych
    łańcuch dostaw
    Opis:
    Cybersecurity has benefitted from Artificial Intelligence (AI) technologies for attack detection. However, recent advances in AI techniques, in tandem with their misuse, have outpaced parallel advancements in cyberattack classification methods that have been achieved through academic and industry-led efforts. We describe the shift in the evolution of AI techniques, and we show how recent AI approaches are effective in helping an adversary attain his/her objectives appertaining to cyberattacks. We also discuss how the current architecture of computer communications enables the development of AI-based adversarial threats against heterogeneous computing platforms and infrastructures.
    Źródło:
    Applied Cybersecurity & Internet Governance; 2022, 1, 1; 1-23
    2956-3119
    2956-4395
    Pojawia się w:
    Applied Cybersecurity & Internet Governance
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A survey of AI imaging techniques for COVID-19 diagnosis and prognosis
    Autorzy:
    Tellakula, K K Praneeth
    Kumar, Saravana
    Deb, Sanjoy
    Powiązania:
    https://bibliotekanauki.pl/articles/1837780.pdf
    Data publikacji:
    2020
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    artificial intelligence
    COVID-19
    diagnosis
    follow-up
    prognosis
    sztuczna inteligencja
    diagnoza
    obserwacja
    prognoza
    Opis:
    The Coronavirus Disease 2019 (COVID-19) has caused massive infections and death toll. Radiological imaging in chest such as computed tomography (CT) has been instrumental in the diagnosis and evaluation of the lung infection which is the common indication in COVID-19 infected patients. The technological advances in artificial intelligence (AI) furthermore increase the performance of imaging tools and support health professionals. CT, Positron Emission Tomography – CT (PET/CT), X-ray, Magnetic Resonance Imaging (MRI), and Lung Ultrasound (LUS) are used for diagnosis, treatment of COVID-19. Applying AI on image acquisition will help automate the process of scanning and providing protection to lab technicians. AI empowered models help radiologists and health experts in making better clinical decisions. We review AI-empowered medical imaging characteristics, image acquisition, computer-aided models that help in the COVID-19 diagnosis, management, and follow-up. Much emphasis is on CT and X-ray with integrated AI, as they are first choice in many hospitals.
    Źródło:
    Applied Computer Science; 2021, 17, 2; 40-55
    1895-3735
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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