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Articles 691 - 720 of 3106
Full-Text Articles in Computer Sciences
Adaptive Blind Equalization For A Mimo Chaotic Communication System, Gökçen Çeti̇nel, Cabi̇r Vural
Adaptive Blind Equalization For A Mimo Chaotic Communication System, Gökçen Çeti̇nel, Cabi̇r Vural
Turkish Journal of Electrical Engineering and Computer Sciences
There exist few blind solutions for chaotic MIMO channel equalization. In this work, a chaotic MIMO channel equalization framework is proposed. The objective function to be minimized in the proposed solution is obtained by adopting the objective function developed for chaotic SISO channel equalization. Furthermore, an optimum filter that minimizes the proposed cost function is designed to recover chaotic input signals assuming that the channel is known. The stationary point of the adaptive solution is equal to the optimal filter if the adaptive filter coefficients change sufficiently slowly. The adaptive solution is contrasted with the optimum filter in terms of …
A Novel Chaos-Based Modulation Scheme: Adaptive Threshold Level Chaotic On-Offkeying For Increased Ber Performance, Kenan Altun, Eni̇s Günay
A Novel Chaos-Based Modulation Scheme: Adaptive Threshold Level Chaotic On-Offkeying For Increased Ber Performance, Kenan Altun, Eni̇s Günay
Turkish Journal of Electrical Engineering and Computer Sciences
A novel modulation scheme called adaptive threshold level-chaotic on?off keying (ATL-COOK) is proposed. This scheme is applied to direct chaotic communication (DCC) systems where the chaotic signals are used as carrier signals. The objective of the proposed adaptive method is to increase the low BER versus SNR performance caused by the constant threshold voltage level. In the proposed method, the communication signal received by the receiver circuits was defined as a Dirac delta function and a comparison signal was obtained from this signal. Then the BER versus SNR performance was analyzed and compared with that of various chaotic generator structures …
Towards Human Activity Recognition For Ubiquitous Health Care Using Data From Awaist-Mounted Smartphone, Umar Zia, Wajeeha Khalil, Salabat Khan, Iftikhar Ahmad, Naeem Khatak
Towards Human Activity Recognition For Ubiquitous Health Care Using Data From Awaist-Mounted Smartphone, Umar Zia, Wajeeha Khalil, Salabat Khan, Iftikhar Ahmad, Naeem Khatak
Turkish Journal of Electrical Engineering and Computer Sciences
Understanding human activities is a newly emerging paradigm that is greatly involved in developing ubiquitous health care (u-Health) systems. The aim of these systems is to seamlessly gather knowledge about the patient?s health and, after collecting knowledge, make suggestions to the patient according to his/her health profile. For this purpose, one of the most important ubiquitous communication trends is the smartphone, which has drawn the attention of both professionals and caregivers for monitoring the aging population, childcare, fall detection, and cognitive impairment. Recognizing human actions in a ubiquitous environment is very challenging and researchers have extensively investigated different methods to …
A Modified Relay-Race Algorithm For Floorplanning In Pcb And Ic Design, Mert Vatansever, İsmai̇l Fai̇k Başkaya
A Modified Relay-Race Algorithm For Floorplanning In Pcb And Ic Design, Mert Vatansever, İsmai̇l Fai̇k Başkaya
Turkish Journal of Electrical Engineering and Computer Sciences
Floorplanning is a fundamental design step in the physical design of printed circuit boards (PCBs) and integrated circuits (ICs), as it handles the complexity of layout design. From a computational point of view, the floorplanning problem is an NP hard problem, and the size of the search space grows exponentially with increasing numbers of modules. Thus, the algorithm used is an essential factor for speed and quality of the floorplanning process. Although polynomial-time floorplanning algorithms can be implemented when solution space is limited to slicing floorplans, optimal solutions often exist only in the nonslicing floorplan search space. Various stochastic algorithms …
Optimal Design Of A Flux Reversal Permanent Magnet Machine As A Wind Turbinegenerator, Majid Ghasemian, Farzad Tahami, Zahra Nasiri-Gheidari
Optimal Design Of A Flux Reversal Permanent Magnet Machine As A Wind Turbinegenerator, Majid Ghasemian, Farzad Tahami, Zahra Nasiri-Gheidari
Turkish Journal of Electrical Engineering and Computer Sciences
Flux reversal permanent magnet generators are well suited for use as wind turbine generators owing to their high torque generation ability and magnetic gear. However, they suffer from poor voltage regulation due to their high winding inductance. In this paper, a design optimization method is proposed for flux reversal generators in wind turbine applications. The proposed method includes a new multiobjective function. Cost, volume of the generator, and mass of the permanent magnet are considered in it independently and simultaneously. Besides the new objective function, the main superiority of this paper compared with published papers is considering winding inductance in …
Geographic Variation And Ethnicity In Diabetic Retinopathy Detection Via Deeplearning, Ali Serener, Sertan Serte
Geographic Variation And Ethnicity In Diabetic Retinopathy Detection Via Deeplearning, Ali Serener, Sertan Serte
Turkish Journal of Electrical Engineering and Computer Sciences
The prevalence of diabetes is on the rise steadily around the globe. Diabetic retinopathy (DR) is a result of damage to the blood vessels in the retina due to diabetes and its fast treatment is crucial for preventing possible blindness. The diagnosis of DR is done mostly using a comprehensive eye exam, where the eye is dilated for better inspection. Analysis by an ophthalmologist is prone to human error and thus automatic and highly accurate detection of DR is preferred for an earlier and better diagnosis. It is important, however, that automatic detection be accurate for all data collected from …
Novel Random Models Of Entity Mobility Models And Performance Analysis Ofrandom Entity Mobility Models, Meti̇n Bi̇lgi̇n
Novel Random Models Of Entity Mobility Models And Performance Analysis Ofrandom Entity Mobility Models, Meti̇n Bi̇lgi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
It has become possible to collect data from geographically large areas with smart devices that are prevalently used today. Sensors that are integrated into smart devices make it possible for these devices to receive and transmit data wirelessly. The most important problem of this model that is known as mobile crowd sensing and that allows inferences on the data obtained from its users is lack of data. The main reason for this problem is the lack of sufficient usage of the sensors on devices by the user. To increase the amount of data collected, while users may be incentivized in …
Hubble: An Optical Link Management System For Dense Wavelength Divisionmultiplexing Networks, Yekta Türk, Engi̇n Zeydan, İbrahi̇m Fati̇h Merci̇mek, Engi̇n Danişman
Hubble: An Optical Link Management System For Dense Wavelength Divisionmultiplexing Networks, Yekta Türk, Engi̇n Zeydan, İbrahi̇m Fati̇h Merci̇mek, Engi̇n Danişman
Turkish Journal of Electrical Engineering and Computer Sciences
Timely detection of Dense Wavelength Division Multiplexing (DWDM) link quality and service performance problems of fiber deployment are important and critical for telecommunication operators. In this paper, we propose a new methodology for network fault detection inside optical transmission systems deployed in a real-operator environment and present the working principles of the system. Our new calculation methodology is used for joint fiber and DWDM link quality evaluation inside the proposed High-level Unified BackBone Link Examiner (HUBBLE) platform. At the end of the paper, we also detail some of the benefits, challenges, and opportunities of automation in DWDM networks using the …
An Inter-Domain Attack Mitigating Solution, Gökhan Akin, Ozan Bük, Erdem Uçar
An Inter-Domain Attack Mitigating Solution, Gökhan Akin, Ozan Bük, Erdem Uçar
Turkish Journal of Electrical Engineering and Computer Sciences
Online services on the Internet are increasing day by day, and in parallel, the number of cyber-attacks is rapidly increasing. These attacks are not always about data theft, but they can cause severe damage by denial of service attacks. Intrusion Prevention System products that many organizations use at the border of their enterprise networks are not strong enough to protect against DoS attacks. The typical way to mitigate such attacks is to get support from a service provider. However, a service provider only provides solutions for the traffic originating from itself. If the source of attack is in another ISP …
A Multibeam Subarrayed Time-Modulated Linear Array, Uğur Yeşi̇lyurt, İhsan Kanbaz, Ertuğrul Aksoy
A Multibeam Subarrayed Time-Modulated Linear Array, Uğur Yeşi̇lyurt, İhsan Kanbaz, Ertuğrul Aksoy
Turkish Journal of Electrical Engineering and Computer Sciences
In conventional time-modulated arrays (TMAs), because of the usage of the RF-switch, harmonics are generated at multiples of the modulation frequency. In this study, the synthesis of time-modulated arrays has been analyzed for cognitive radio (CR) systems, in which these harmonics are suitably exploited for more efficient utilization of the spectrum. In order to accomplish the desired pattern at requested harmonic frequencies, a new excitation strategy with sinusoidal signals is proposed. The use of sinusoidal waveforms creates independent beams, allowing independent steering capability. Moreover, by utilizing the subarray structure, it is possible to have a smaller number of excitation functions …
Hyperheuristics For Explicit Resource Partitioning In Simultaneous Multithreadedprocessors, İsa Ahmet Güney, Kemal Poyraz, Gürhan Küçük, Ender Özcan
Hyperheuristics For Explicit Resource Partitioning In Simultaneous Multithreadedprocessors, İsa Ahmet Güney, Kemal Poyraz, Gürhan Küçük, Ender Özcan
Turkish Journal of Electrical Engineering and Computer Sciences
In simultaneous multithreaded (SMT) processors, various data path resources are concurrently shared by many threads. A few heuristic approaches that explicitly distribute those resources among threads with the goal of improved overall performance have already been proposed. A selection hyperheuristic is a high-level search methodology that mixes a predetermined set of heuristics in an iterative framework to utilize their strengths for solving a given problem instance. In this study, we propose a set of selection hyperheuristics for selecting and executing the heuristic with the best performance at a given stage. To the best of our knowledge, this is one of …
Event-Based Summarization Of News Articles, Feri̇de Savaroğlu Tabak, Vesi̇le Evri̇m
Event-Based Summarization Of News Articles, Feri̇de Savaroğlu Tabak, Vesi̇le Evri̇m
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, with the increase of available digital information on the Web, the time needed to find relevant information is also increased. Therefore, to reduce the time spent on searching, research on automatic text summarization has gained importance. The proposed summarization process is based on event extraction methods and is called an event-based extractive single-document summarization. In this method, the important features of event extraction and summarization methods are analyzed and combined together to extract the summaries from single-source news documents. Among the tested features, six features are found to be the most effective in constructing good summaries. The …
Design Of A Low Pass Filter Using Rhombus-Shaped Resonators With An Analyticallc Equivalent Circuit, Mohsen Hookari, Saeed Roshani, Sobhan Roshani
Design Of A Low Pass Filter Using Rhombus-Shaped Resonators With An Analyticallc Equivalent Circuit, Mohsen Hookari, Saeed Roshani, Sobhan Roshani
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a new method is presented for the design of a low pass filter (LPF) based on an LC equivalent circuit. Firstly, new formulas are proposed to calculate an LC equivalent circuit of a rhombus-shaped resonator. Secondly, the transfer function and transmission zero of the rhombus-shaped resonator are extracted, based on the presented formulas. Then other rhombus-shaped resonators are designed, based on the extracted formulas. The proposed filter has a cut-off frequency with an attenuation level of 3 dB at 1.54 GHz. The obtained return loss and insertion loss in the pass band are 16 dB and 0.1 …
Ternary Logical Naming Convention And Application In Ternary Optical Computers, Shuang Li, Yi Jin
Ternary Logical Naming Convention And Application In Ternary Optical Computers, Shuang Li, Yi Jin
Turkish Journal of Electrical Engineering and Computer Sciences
This article introduces the ternary logical naming convention, which was newly discovered in the study of logical units of ternary optical computers (TOCs). First, the design principle and design specification of the ternary logical naming convention are elaborated in detail and several examples are given to illustrate the use of the naming convention. Second, taking the modified signed-digit (MSD) adder of the TOC as an example, the naming convention is applied to build four ternary logical units of the MSD adder, and the implementation method of pipelined addition is introduced. Finally, the correctness of the ternary logical naming convention proposed …
An Automated Eye Disease Recognition System From Visual Content Of Facial Imagesusing Machine Learning Techniques, Ashrafi Akram, Rameswar Debnath
An Automated Eye Disease Recognition System From Visual Content Of Facial Imagesusing Machine Learning Techniques, Ashrafi Akram, Rameswar Debnath
Turkish Journal of Electrical Engineering and Computer Sciences
Many eye diseases like cataracts, trachoma, or corneal ulcer can cause vision problems. Progression of these eye diseases can only be prevented if they are recognized accurately at the early stage. Visually observable symptoms differ a lot among these eye diseases. However, a wide variety of symptoms is necessary to be analyzed for the accurate detection of eye diseases. In this paper, we propose a novel approach to provide an automated eye disease recognition system using visually observable symptoms applying digital image processing techniques and machine learning techniques such as deep convolution neural network (DCNN) and support vector machine (SVM). …
Multitask-Based Association Rule Mining, Peli̇n Yildirim Taşer, Kökten Ulaş Bi̇rant, Derya Bi̇rant
Multitask-Based Association Rule Mining, Peli̇n Yildirim Taşer, Kökten Ulaş Bi̇rant, Derya Bi̇rant
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, there has been a growing interest in association rule mining (ARM) in various fields. However, standard ARM algorithms fail to discover rules for multitask problems as they do not consider task-oriented investigation and, therefore, they ignore the correlation among the tasks. Considering this situation, this paper proposes a novel algorithm, named multitask association rule miner (MTARM), that tends to jointly discover rules by considering multiple tasks. This paper also introduces two novel concepts: single-task rule and multiple-task rule. In the first phase of the proposed approach, highly frequent local rules (single-task rules) are explored for each task separately and …
Adaptive Prescribed Performance Servo Control Of An Automotive Electronicthrottle System With Actuator Constraint, Zitao Sun, Xiaohong Jiao
Adaptive Prescribed Performance Servo Control Of An Automotive Electronicthrottle System With Actuator Constraint, Zitao Sun, Xiaohong Jiao
Turkish Journal of Electrical Engineering and Computer Sciences
To further improve the transient and steady-state performance of automotive electronic throttle position tracking, in this paper an adaptive prescribed performance servo control strategy is designed and applied to a real electronic throttle control system. In view of the possible high gain of the prescribed performance controller in practice, the actuator constraint is also considered in the controller design. The designed servo controller can ensure the transient and steady-state responses of tracking error are limited in the range prescribed by the performance function, and converge with the prescribed convergence rate and have no overshoot. The incorporated adaptive updating law can …
A Fast Text Similarity Measure For Large Document Collections Using Multireference Cosine And Genetic Algorithm, Hamid Mohammadi, Seyed Hossein Khasteh
A Fast Text Similarity Measure For Large Document Collections Using Multireference Cosine And Genetic Algorithm, Hamid Mohammadi, Seyed Hossein Khasteh
Turkish Journal of Electrical Engineering and Computer Sciences
One of the critical factors that make a search engine fast and accurate is a concise and duplicate free index. In order to remove duplicate and near-duplicate (DND) documents from the index, a search engine needs a swift and reliable DND text document detection system. Traditional approaches to this problem, such as brute force comparisons or simple hash-based algorithms, are not suitable as they are not scalable and are not capable of detecting near-duplicate documents effectively. In this paper, a new signature-based approach to text similarity detection is introduced, which is fast, scalable, and reliable and needs less storage space. …
Accurate Indoor Positioning With Ultra-Wide Band Sensors, Taner Arsan
Accurate Indoor Positioning With Ultra-Wide Band Sensors, Taner Arsan
Turkish Journal of Electrical Engineering and Computer Sciences
Ultra-wide band is one of the emerging indoor positioning technologies. In the application phase, accuracy and interference are important criteria of indoor positioning systems. Not only the method used in positioning, but also the algorithms used in improving the accuracy is a key factor. In this paper, we tried to eliminate the effects of off-set and noise in the data of the ultra-wide band sensor-based indoor positioning system. For this purpose, optimization algorithms and filters have been applied to the raw data, and the accuracy has been improved. A test bed with the dimensions of 7.35 m × 5.41 m …
Prediction Of Railway Switch Point Failures By Artificial Intelligence Methods, Burak Arslan, Hasan Ti̇ryaki̇
Prediction Of Railway Switch Point Failures By Artificial Intelligence Methods, Burak Arslan, Hasan Ti̇ryaki̇
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, railway transport has been preferred intensively in local and intercity freight and passenger transport. For this reason, it is of utmost importance that railway lines are operated in an uninterrupted and safe manner. In order to carry out continuous operation, all systems must continue to operate with maximum availability. In this study, data were collected from switch motors, which are the important equipment of railways, and the related equipment and these data were evaluated with sector experience and the results related to the failure status of the switch points were revealed. The obtained results were processed with …
A Viable Snore Detection System: Hardware And Software Implementations, Ahmet Turgut Tuncer, Mehmet Bi̇lgen
A Viable Snore Detection System: Hardware And Software Implementations, Ahmet Turgut Tuncer, Mehmet Bi̇lgen
Turkish Journal of Electrical Engineering and Computer Sciences
A stand-alone, custom-made biomedical system was introduced for long-term monitoring of sleep and detection of snoring events. Commercially available electronic components were assembled for recording audio, pulse, and respiration signals. Its software was implemented for off-line processing of the acquired signals in C++ and MATLAB environments. The linear and nonlinear features of the signals were extracted and characterized using spectral energy distribution, entropy, and largest Lyapunov exponent (LLE). The performance of the system was evaluated with real physiological data gathered from 14 chronic snorers. Analysis of the cases indicated that the system identified the snoring events with an accuracy of …
Estimating Spatiotemporal Focus Of Documents Using Entropy With Pmi, Damla Yaşar, Selma Teki̇r
Estimating Spatiotemporal Focus Of Documents Using Entropy With Pmi, Damla Yaşar, Selma Teki̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Many text documents are spatiotemporal in nature, i.e. contents of a document can be mapped to a specific time period or location. For example, a news article about the French Revolution can be mapped to year 1789 as time and France as place. Identifying this time period and location associated with the document can be useful for various downstream applications such as document reasoning or spatiotemporal information retrieval. In this paper, temporal entropy with pointwise mutual information (PMI) is proposed to estimate the temporal focus of a document. PMI is used to measure the association of words with time expressions. …
Satire Identification In Turkish News Articles Based On Ensemble Of Classifiers, Aytuğ Onan, Mansur Alp Toçoğlu
Satire Identification In Turkish News Articles Based On Ensemble Of Classifiers, Aytuğ Onan, Mansur Alp Toçoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Social media and microblogging platforms generally contain elements of figurative and nonliteral language, including satire. The identification of figurative language is a fundamental task for sentiment analysis. It will not be possible to obtain sentiment analysis methods with high classification accuracy if elements of figurative language have not been properly identified. Satirical text is a kind of figurative language, in which irony and humor have been utilized to ridicule or criticize an event or entity. Satirical news is a pervasive issue on social media platforms, which can be deceptive and harmful. This paper presents an ensemble scheme for satirical news …
Crash Course Learning: An Automated Approach To Simulation-Driven Lidar-Basedtraining Of Neural Networks For Obstacle Avoidance In Mobile Robotics, Stanko Kruzic, Josip Music, Mirjana Bonkovic, Frantisek Duchon
Crash Course Learning: An Automated Approach To Simulation-Driven Lidar-Basedtraining Of Neural Networks For Obstacle Avoidance In Mobile Robotics, Stanko Kruzic, Josip Music, Mirjana Bonkovic, Frantisek Duchon
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes and implements a self-supervised simulation-driven approach to data collection used for training of perception-based shallow neural networks for mobile robot obstacle avoidance. In the approach, a 2D LiDAR sensor was used as an information source for training neural networks. The paper analyzes neural network performance in terms of numbers of layers and neurons, as well as the amount of data needed for reliable robot operation. Once the best architecture is identified, it is trained using only data obtained in simulation and then implemented and tested on a real robot (Turtlebot 2) in several simulations and real-world scenarios. …
Convolutional Auto Encoders For Sentence Representation Generation, Ali̇ Mert Ceylan, Vecdi̇ Aytaç
Convolutional Auto Encoders For Sentence Representation Generation, Ali̇ Mert Ceylan, Vecdi̇ Aytaç
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we have proposed an alternative approach for sentence modeling problem. The difficulty of the choice of answer, the semantically related questions and the lack of syntactic closeness of the answers give rise to the difficulty of selecting the answer. The deep learning field has recently achieved a pivotal success in semantic analysis, machine translation, and text summaries. The essence of this work, inspired by the human orthographic processing mechanism and using multiple convolution filters with pre-rendered 2-Dimension (2D) representations of sentences, input or output size is to learn the basic features of the language without concerns. For …
Measurement Based Threat Aware Drone Base Station Deployment, Alper Akarsu, Tolga Gi̇ri̇ci̇
Measurement Based Threat Aware Drone Base Station Deployment, Alper Akarsu, Tolga Gi̇ri̇ci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Unmanned aerial vehicles are gaining importance with many civilian and military applications. Especially the surveillance, search/rescue, and military operations may have to be carried out in extremely constrained environments. In such scenarios, drone base stations (DBSs) have to provide communication services to the people at the ground. The ground users may have no access to the global positioning system (GPS); therefore, their locations have to be estimated using alternative techniques. Besides there may be threats in the environment, such as shooters. In this work, we address the problem of optimal DBS deployment under the aforementioned constraints. We propose a novel …
A Population Based Simulated Annealing Algorithm For Capacitated Vehicle Routing Problem, İlhan İlhan
A Population Based Simulated Annealing Algorithm For Capacitated Vehicle Routing Problem, İlhan İlhan
Turkish Journal of Electrical Engineering and Computer Sciences
The Vehicle Routing Problem (VRP) is one of the most discussed and researched topics nowadays. The VRP is briefly defined as the problem of identifying the best route to reduce distribution costs and improve the quality of service provided to customers. The Capacitated VRP (CVRP) is one of the most commonly researched among the VRP types. Therefore, the CVRP was studied in this paper and a new population based simulated annealing algorithm was proposed. In the algorithm, three different route development operators were used, which are exchange, insertion and reversion operators. It was tested on 63 well-known benchmark instances in …
Comparisons Of Extreme Learning Machine And Backpropagation-Based I-Vector Approach For Speaker Identification, Musab T S Al-Kaltakchi, Raid Rafi Omar Al-Nima, Mohammed A M Abdullah
Comparisons Of Extreme Learning Machine And Backpropagation-Based I-Vector Approach For Speaker Identification, Musab T S Al-Kaltakchi, Raid Rafi Omar Al-Nima, Mohammed A M Abdullah
Turkish Journal of Electrical Engineering and Computer Sciences
The extreme learning machine (ELM) is one of the machine learning applications used for regression and classification systems. In this paper, an extended comparison between an ELM and the backpropagation neural network (BPNN)-based i-vector is given in terms of a closed-set speaker identification task using 120 speakers from the TIMIT database. The system is composed of the mel frequency cepstal coefficient (MFCC) and power normalized cepstal coefficient (PNCC) approaches to form the feature extraction stage, while the cepstral mean variance normalization (CMVN) and feature warping are applied in order to mitigate the linear channel effect. The system is utilized with …
Design Of A Spurious-Free Rf Frequency Synthesizer For Fast-Settling Receivers, Hi̇lmi̇ Kayhan Yilmaz, Serkan Topaloğlu
Design Of A Spurious-Free Rf Frequency Synthesizer For Fast-Settling Receivers, Hi̇lmi̇ Kayhan Yilmaz, Serkan Topaloğlu
Turkish Journal of Electrical Engineering and Computer Sciences
A tunable reference clock frequency topology is presented as a spur reduction application for frequency synthesizers of fast frequency hopping spread spectrum systems. The method was verified by measurements on a designed hardware operating at L-band frequencies. This spur reduction method is based on optimizing the reference clock frequency of synthesizers to mitigate spurs. By using the spur reduction method, the power of spurious signals was reduced up to 57 dB. The performance of the spur reduction method was also analyzed at different loop-filter configurations. Smaller lock time was obtained by enlarging the bandwidth of the loop filter up to …
Optimization Of Real-World Outdoor Campaign Allocations, Fatmanur Akdoğan Uzun, Doğan Altan, Ercan Peker, Mahmut Altuğ Üstün, Sanem Sariel
Optimization Of Real-World Outdoor Campaign Allocations, Fatmanur Akdoğan Uzun, Doğan Altan, Ercan Peker, Mahmut Altuğ Üstün, Sanem Sariel
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we investigate the outdoor campaign allocation problem (OCAP), which asks for the distribution of campaign items to billboards considering a number of constraints. In particular, for a metropolitan city with a large number of billboards, the problem becomes challenging. We propose a genetic algorithm-based method to allocate campaign items effectively, and we compare our results with those of nonlinear integer programming and greedy approaches. Real-world data sets are collected with the given constraints of the price class ratios of billboards located in İstanbul and the budgets of the given campaigns. The methods are evaluated in terms of …