https://hdl.handle.net/20.500.12294/370 Bilgisayar Programcılığı Programına ait koleksiyonlar bu alt bölümde listelenir. Fri, 22 May 2026 20:26:52 GMT 2026-05-22T20:26:52Z https://hdl.handle.net/20.500.12294/4101 Vibrational Genetic Algorithm-Based Deployment of Wireless Sensor Networks With Heterogeneous Nodes in Irregularly Shaped Areas Birtane, Sibel; Sahingoz, Ozgur Koray; Korkmaz, Hayriye Over the past few years, there has been a significant emphasis on improving the capabilities of Wireless Sensor Networks (WSNs) by making advancements in communication protocols, energy efficiency, optimal deployment, data analytics, and integration with emerging technologies, such as the Internet of Things and artificial intelligence. The deployment of WSN nodes can greatly enhance the effectiveness, scalability, and capability of different systems, resulting in cost reductions, enhanced performance, and improved safety in which the deployment of WSN involves determining the best positioning of sensor nodes to attain maximum coverage and connectivity while minimizing the number of nodes needed. WSNs often face challenges in deploying nodes effectively and Genetic Algorithms (GAs) offer a valuable approach for tackling this problem due to their ability to efficiently search large and complex solution spaces, such as those of complex network design, taking into account various constraints and objectives, which are common characteristics of real-world WSN deployment scenarios. The objective of this study is to use a new method, called the vibrational genetic algorithm, which can be used to optimize the placement of sensor nodes more efficiently. Apart from the other research, it is preferred to use heterogeneous sensor nodes to increase the coverage rate in an irregularly shaped area. The results of the experiments demonstrate that the proposed model offers an effective solution for achieving maximum coverage in application theaters that are more realistic and complex. Mon, 01 Jan 2024 00:00:00 GMT https://hdl.handle.net/20.500.12294/4101 2024-01-01T00:00:00Z https://hdl.handle.net/20.500.12294/3249 Gaussian Applications in Organic Structured Electronic Systems Idman, Ebru; Idman, Emrah; Yildirim, Osman The purpose of this research is to explore the molecular energy of organic structures in the form of nanoparticles with Gaussian W09 software. For this purpose, the structures of 2PANI ES-X in the literature were analyzed with Gaussian W09. Organic semiconductors have been explored since the last 60 years [1]. Ching W. Tang was first considered the father of organic electronics, since he found the organic light emitting diode (OLED) in the 1980s. Tang later broke ground to produce organic solar cells with his OLED research [2]-[3]. Subsequent studies investigated organic electroluminescence, organic photovoltaic cells, effective transistors that received organic thin film, and organic transistor models were developed [4]-[6]. It is known that they have the potential to be used in conductive polymers, sensors, energy converter, rechargeable batteries, photochemical cells, batteries and fuel cells, electrochromic tools and ion selective electrodes, and a protective cover against electromagnetic interference. In summary, conductive polymers will be the conductors of the future. © 2020 IEEE. Wed, 01 Jan 2020 00:00:00 GMT https://hdl.handle.net/20.500.12294/3249 2020-01-01T00:00:00Z https://hdl.handle.net/20.500.12294/2036 Solving asymmetric traveling salesman problem using genetic algorithm Birtane Akar, Sibel; Şahingöz, O.K. This study describes the genetic algorithm method that is most commonly used in search and optimization studies with solution approach of the asymmetric travelling salesman problem, which is the leading problem of the complex problems and a different model of the traveling salesman problem. The proposed system has been put forward the test results and the system has been shown to provide an acceptable period of time with an effective solution environment. © 2015 IEEE. 2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 -- 16 May 2015 through 19 May 2015 -- Thu, 01 Jan 2015 00:00:00 GMT https://hdl.handle.net/20.500.12294/2036 2015-01-01T00:00:00Z https://hdl.handle.net/20.500.12294/2010 A multi agent solution for UAV path planning problem with NetLogo Çalık Kazdal, Seda; Kuğu, Emin; Birtane, Sibel; Şahingöz, Özgür Koray Due to its low cost, small size, autonomous structure and high mobility, usage of the Unmanned Aerial Vehicles (UAVs) has been increasing over the last two decades. To construct an autonomous UAV, path planning is a crucial task to meet the objectives specified for the mission. Mainly, the purpose of path planning can be described as find the optimal path from a start point to the destination point to check necessary control points (CPs) while taking into consideration different operational constraints. While the number of CPs increases, constructing an optimal path is getting trivial, most of the researchers used evolutionary algorithms and/or swarm algorithms to reach a near optimal solution in an acceptable time. In this study, it is aimed to solve the UAV Path Planning problem with a swarm intelligence algorithm as Ant Colony Optimization Algorithm. To implement this algorithm with similar to the real world, each ant is aimed to implement as an autonomous agent, and the proposed system is implemented on NetLogo, which is a multi-agent programmable modeling environment for simulating real World problems. The experimental results showed that the proposed system produces an acceptable solution in a limited time. © Research India Publications. #nofulltext# --- Birtane, Sibel (Arel Author) Fri, 01 Jan 2016 00:00:00 GMT https://hdl.handle.net/20.500.12294/2010 2016-01-01T00:00:00Z