Artificial neural networks for transfer aligment and calibration of inertial navigation systems

Artificial intelligence applications in earthquake resistant architectural design: Determination of irregular structural systems with deep learning and ImageAI method Bingol, Kaan; Akan, Asli Er; ÖRMECİOĞLU, HİLAL TUĞBA; ER, ARZU (Journal of the Faculty of Engineering and Architecture of Gazi University, 2020-01-01) Although the architectural design process is carried out with the collaboration of experts who are experienced in many different areas from the main preferences to the detailing stage, the major decisions such as plan organization, mass design etc. are taken by the architect. Computer Aided Design (CAD) programs are generally effective after the major decisions of the design are taken. For this reason, it is common for the main decisions, taken during the design process, to be changed during the analysis of...
Structured neural networks for modeling and identification of nonlinear mechanical systems Kılıç, Ergin; Dölen, Melik; Koku, Ahmet Buğra; Department of Mechanical Engineering (2012) Most engineering systems are highly nonlinear in nature and thus one could not develop efficient mathematical models for these systems. Artificial neural networks, which are used in estimation, filtering, identification and control in technical literature, are considered as universal modeling and functional approximation tools. Unfortunately, developing a well trained monolithic type neural network (with many free parameters/weights) is known to be a daunting task since the process of loading a specific pat...
Artificial Neural Network Models for Forecasting Tourist Arrivals to Barcelona Alptekin, Bülent; ALADAĞ, ÇAĞDAŞ HAKAN (2016-09-09) In order to reach accurate tourism demand forecasts, various forecasting methods have been proposed in the literature [1]. These approaches can be divided into two subclasses. One of them is conventional methods such as autoregressive moving average (ARIMA) or exponential smoothing. And, the other one is advanced forecasting techniques such as fuzzy time series, artificial neural networks (ANN) or hybrid approaches. The main purpose of this study is to develop some efficient forecasting models based on ANN ...
Intelligent methods for dynamic analysis and navigation of autonomous land vehicles Kaygısız, Hüseyin Burak; Erkmen, Aydan Müşerref; Department of Electrical and Electronics Engineering (2004) Autonomous land vehicles (ALVs) have received considerable attention after their introduction into military and commercial applications. ALVs still stand as a challenging research topic. One of the main problems arising in ALV operations is the navigation accuracy while the other is the dynamic effects of road irregularities which may prevent the vehicle and its cargo to function properly. In this thesis, we propose intelligent solutions to these two basic problems of ALV. First, an intelligent method is pr...
ARTIFICIAL LEARNING-BASED ANALYSIS OF MOLECULAR, CLINICAL TRIALS AND PATENT DATA FOR IMPROVED DRUG DEVELOPMENT Çıray, Fulya; Aydın Son, Yeşim; Doğan, Tunca; Department of Medical Informatics (2022-8-31) Drug development is a costly process, especially in terms of the required time and money. Many promising drug candidates are eliminated at late development stages, e.g., phase II or III of clinical trials, due to insufficient efficacy or unexpected adverse health related affects. Lately, pharmaceutical companies are evaluating computational approaches, to increase the efficiency of this process. In this thesis study, we investigated the computational prediction of the approval of drug candidate compounds by...

Citation Formats

O. Tekinalp, “Artificial neural networks for transfer aligment and calibration of inertial navigation systems,” 2001, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69442.