Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Publisher: search.filters.publisher.Elsevier Ltd.Subject: search.filters.subject.Artificial intelligence

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  • Article
    Citation - WoS: 31
    Citation - Scopus: 34
    Data Pre-Post Processing Methods in Ai-Based Modeling of Seepage Through Earthen Dams
    (Elsevier Ltd., 2019) Sharghi, Elnaz; Nourani, Vahid; Behfar, Nazanin; Tayfur, Gökmen
    In this paper, seepage of Sattarkhan earthen dam in northwest Iran was simulated using various artificial intelligence (AI) models (e.g., Feed forward neural network, Adaptive neural fuzzy inference system and Support vector regression) and linear ARIMA model based on different input combinations. Both jittering pre-processing and ensembling post-processing methods were also used in order to enhance the performance of the used AI-based data driven methods. For this purpose, various jittered datasets were produced by imposing noises (at different levels) to the original time series to enlarge the training data sample space. Further, three techniques of simple linear, weighted linear and nonlinear neural averaging were considered for pre-post processing purpose. The obtained results indicated that using both jittering and ensembling (especially neural ensemble) enhanced the modeling performance by almost 30% in the testing phase. (C) 2019 Elsevier Ltd. All rights reserved.
  • Article
    Citation - Scopus: 1
    Cost Effective Localization in Distributed Sensory Networks
    (Elsevier Ltd., 2011) Coşkun, Anıl; Sevil, Hakkı Erhan; Özdemir, Serhan
    The most important mechanism to occur in biological distributed sensory networks (DSNs) is called lateral inhibition, (LI). LI relies on one simple principle. Each sensor strives to suppress its neighbors in proportion to its own excitation. In this study, LI mechanism is exploited to localize the unknown position of a light source that illuminated the photosensitive sensory network containing high and low quality sensors. Each photosensitive sensor was then calibrated to accurately read the distance to the light source. A series of experiments were conducted employing both quality sensors. Low quality array was allowed to take advantage of LI, whereas the high quality one was not. Results showed that the lateral inhibition mechanism increased the sensitivity of inferior quality sensors, giving the ability to make the localization as sensitive as high quality sensors do. This suggests that the networks with multitude of sensors could be made cost-effective, were these sensory networks equipped with LI.