Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 8Citation - Scopus: 14An End-To Trainable Feature Selection-Forecasting Architecture Targeted at the Internet of Things(IEEE, 2021) Nakıp, Mert; Karakayalı, Kubilay; Güzeliş, Cüneyt; Rodoplu, VolkanWe develop a novel end-to-end trainable feature selection-forecasting (FSF) architecture for predictive networks targeted at the Internet of Things (IoT). In contrast with the existing filter-based, wrapper-based and embedded feature selection methods, our architecture enables the automatic selection of features dynamically based on feature importance score calculation and gamma-gated feature selection units that are trained jointly and end-to-end with the forecaster. We compare the performance of our FSF architecture on the problem of forecasting IoT device traffic against the following existing (feature selection, forecasting) technique pairs: Autocorrelation Function (ACF), Analysis of Variance (ANOVA), Recurrent Feature Elimination (RFE) and Ridge Regression methods for feature selection, and Linear Regression, Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM), 1 Dimensional Convolutional Neural Network (1D CNN), Autoregressive Integrated Moving Average (ARIMA), and Logistic Regression for forecasting. We show that our FSF architecture achieves either the best or close to the best performance among all of the competing techniques by virtue of its dynamic, automatic feature selection capability. In addition, we demonstrate that both the training time and the execution time of FSF are reasonable for IoT applications. This work represents a milestone for the development of predictive networks for IoT in smart cities of the near future.Conference Object Citation - WoS: 3Citation - Scopus: 3Design of Adaptive Structures by Kinematic Synthesis of Mechanisms(CRC Press, 2013) Akgün, Yenal; Maden, Feray; Korkmaz, KorayParallel to the development of material science and computer technologies, adaptive structures and smart building components have become the demand of contemporary architecture. However, in order to design adaptive systems, basic knowledge on kinematic synthesis is needed. This paper introduces the fundamental principles of the kinematic synthesis of mechanisms and expresses the potential structural uses of common mechanisms. For this purpose, main concepts of the mechanisms are introduced and types of kinematic synthesis are explored by the help of innovative examples. In this context, firstly, type synthesis methods are explained. Second step covers the path generation rules, and the final step includes the design of multi-loop and chain mechanisms. During the explanation of the aforementioned principles, innovative adaptive structures which are designed by the authors are introduced as well. These structures are all derived from common planar and spatial mechanisms such as four-bar linkages, Watt mechanisms, scissor systems, Bennett linkages and different multi-loop mechanisms.