Teknik Bilimler Meslek Yüksekokulu / Vocational School of Technical Sciences

Permanent URI for this collectionhttps://hdl.handle.net/11727/2031

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Author: search.filters.author.Tartan, Emre OnerStart date: 2013

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Now showing 1 - 7 of 7
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    Sequential Decision Making for Elevator Control
    (2023) Tartan, Emre Oner; Ciflikli, Cebrail; 0000-0002-5688-4226; JVD-9650-2023
    In the last decade Reinforcement Learning (RL) has significantly changed the conventional control paradigm in many fields. RL approach is spreading with many applications such as autonomous driving and industry automation. Markov Decision Process (MDP) forms a mathematical idealized basis for RL if the explicit model is available. Dynamic programming allows to find an optimal policy for sequential decision making in a MDP. In this study we consider the elevator control as a sequential decision making problem, describe it as a MDP with finite state space and solve it using dynamic programming. At each decision making time step we aim to take the optimal action to minimize the total of hall call waiting times in the episodic task. We consider a sample 6-floor building and simulate the proposed method in comparison with the conventional Nearest Car Method (NCM).
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    Optimization of Waiting and Journey Time in Group Elevator System Using Genetic Algorithm
    (2014) Tartan, Emre Oner; Erdem, Hamit; Berkol, Ali
    Efficient elevator group control is an important issue for vertical transportation in high-rise buildings. From the engineering design perspective, regulation of average waiting time and journey time while considering energy consumption is an optimization problem. Alternatively to the conventional algorithms for scheduling and dispatching cars to hall calls, intelligent systems based methods have drawn much attention in the last years. This study aims to improve the elevator group control system's performance by applying genetic algorithm based optimization algorithms considering two systems. Firstly, average passenger waiting time is optimized in the conventional elevator systems in which a hall call is submitted by indicating the travel direction. Secondly, a recent development in elevator industry is considered and it is assumed that instead of direction indicators there are destination button panels at floors that allow passengers to specify their destinations. In this case optimization of average waiting time, journey time and car trip time is investigated. Two proposed algorithms have been applied considering preload conditions in a building with 20 floors and 4 cars. The simulation results have been compared with a previous study and conventional duplex algorithm.
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    A Simple Population Based Hybrid Harmonic Estimation Algorithm
    (2016) Tartan, Emre Oner; Erdem, Hamit
    This paper presents a new hybrid algorithm for harmonic estimation. The algorithm combines a simple fast population based search algorithm with Least Squares Method. It is based on the structural property of the harmonic estimation problem which implies that the signal model is linear in amplitude and nonlinear in phase. The hybrid algorithm uses the search algorithm for phase estimation and LS for amplitude estimation, iteratively. Exploiting the objective function defined according to the error of single harmonic's phase estimation, the proposed search algorithm distributes the population through equal intervals and simply narrows the search space sequentially in every generation. Unlike the other heuristic optimization algorithms that uses random distribution in initialization stage, the proposed method provides more robust convergence in the limits determined by the generation number. Simulation results show that the proposed hybrid algorithm not only gives accurate results but also significantly improves the computation time when compared with other heuristic optimization algorithms. Moreover this approach can be used to reduce the search duration when involved in other evolutionary optimization algorithms in a hybrid way and then can deal with frequency deviation and subharmonic estimation which are pitfalls for DFT based algorithms.
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    Elevator Parking Approach in Nearest Car Method
    (2018) Ciflikli, Cebrail; Tartan, Emre Oner
    A fundamental factor that determines the system efficiency and the quality of service in elevator group control systems is the used elevator dispatching algorithm. Along with the elevator dispatching algorithm, using an elevator parking algorithm can provide improvements in the performance of an elevator group control system. In this study considering a system that uses Nearest Car Method as the elevator dispatching algorithm, average passenger waiting time is investigated under different traffic conditions using three parking algorithms and when no parking algorithm is used. For a more efficient elevator control system an adaptive park algorithm which is changing according to varying traffic conditions is proposed.
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    An Android Application for Geolocation Based Health Monitoring, Consultancy And Alarm System
    (2018) Tartan, Emre Oner; Ciflikli, Cebrail
    In the last decade significant progress have been made in smart phone technology as well as in wireless wide area network technologies. Today among a wide population smart phones and mobile applications are considered as indispensable part of daily life. A field that mobile applications have great potential is health monitoring. Health monitoring covers various physiological signals. One of these signals is heart rate which is related to cardiovascular state of the body. Recently producers offer heart rate monitoring with the on board or wearable heart rate sensor. Although the main trend is for individual usage especially in sports, heart rate monitoring can also be benefited in an emergency alarm system for people who have potential risks while doing sports or elderly people. Such a distant monitoring system can be helpful to deliver first aid in emergency cases. Moreover an health expert can monitor states of the patients in real time. In this study we benefit the facilities provided by mobile technology and propose a geolocation-based heart rate monitoring system. The developed mobile application can send alarm message through notification, sms, mail and allows messaging with the health expert for consultancy. Hence if anomalies are observed in heart rate variability during the outdoor activities, emergency information can be delivered in the shortest time and the delays which have crucial affects can be prevented. The same framework can be extended to a more general system including different sensors for monitoring various physiological signals.
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    A model for the visualization and analysis of elevator traffic
    (2019) Ciflikli, Cebrail; Tartan, Emre Oner
    Analysis of elevator traffic in high rise buildings is critical to the performance evaluation of elevator group control systems (EGCS). Elevator dispatching methods or parking algorithms in an EGCS can be designed or modified according to analyses of traffic flow. However, interpretation of traffic flow based solely on numerical data may not be explicit and transparent for EGCS experts as well as for other non-expert building administration. In this study, we present a model for visualization and analysis of elevator traffic. First, we present an alternative approach for traffic analysis which we call route visualization. In the proposed approach, we initially decompose elevator traffic into its component parts and investigate each component independently. Then, using superposition of components we obtain a reconstructed model of overall traffic. This modeling approach provides component-based traffic analysis and representation of routes with intensities through data visualization. In the second part we introduce a multi-dimensional analysis of time parameters in ECGS. This approach provides a comparative analysis of several control algorithms such as dispatch or park algorithms for different combinations of traffic components.
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    Slot Parameter Optimization for Multiband Antenna Performance Improvement Using Intelligent Systems
    (2015) Demircioglu, Erdem; Yagli, Ahmet Fazil; Gulgonul, Senol; Ankishan, Haydar; Tartan, Emre Oner; Sazli, Murat H.; Imeci, Taha
    This paper discusses bandwidth enhancement for multiband microstrip patch antennas (MMPAs) using symmetrical rectangular/square slots etched on the patch and the substrate properties. The slot parameters on MMPA are modeled using soft computing technique of artificial neural networks (ANN). To achieve the best ANN performance, Particle Swarm Optimization (PSO) and Differential Evolution (DE) are applied with ANN's conventional training algorithm in optimization of the modeling performance. In this study, the slot parameters are assumed as slot distance to the radiating patch edge, slot width, and length. Bandwidth enhancement is applied to a formerly designed MMPA fed by a microstrip transmission line attached to the center pin of 50 ohm SMA connecter. The simulated antennas are fabricated and measured. Measurement results are utilized for training the artificial intelligence models. The ANN provides 98% model accuracy for rectangular slots and 97% for square slots; however, ANFIS offer 90% accuracy with lack of resonance frequency tracking.