Yazar "Kiran M.S." seçeneğine göre listele
Listeleniyor 1 - 5 / 5
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe Boundary conditions in tree-seed algorithm: Analysis of the success of search space limitation techniques in tree-seed algorithm(Institute of Electrical and Electronics Engineers Inc., 2017) Çinar A.C.; Kiran M.S.Swarm intelligence or evolutionary computation algorithms search possible solutions in a predetermined search space of an optimization problem. In some cases candidate solutions go out of search space during the search. In such situations, search space limitation techniques or boundary conditions are used for sway up this outcast individual into search space. The boundary conditions are classified two main categories whose names are restricted and unrestricted techniques. Restricted boundary conditions forces outcast individual into search space but unrestricted boundary conditions does not force. In this work we use four restricted boundary conditions whose names are Absorbing, Reflecting, Damping and Randomly. Additionally, three unrestricted boundary conditions (Invisible, Invisible Reflecting and Invisible Damping) are used in the study. These boundary conditions are applied in Tree-Seed Algorithm (TSA). The test material is five standard benchmark functions and these are Sphere, Rastrigin, Rosenbrock, Griewank and Ackley. The main idea of this study is to investigate whether there is a significant difference among the limitation methods in TSA. Experimental results show that there is no significant difference among the boundary conditions methods for TSA. © 2017 IEEE.Öğe An improved tree seed algorithm for optimization problems(International Association of Computer Science and Information Technology, 2018) Aslan M.; Beskirli M.; Kodaz H.; Kiran M.S.Various heuristic algorithms have been proposed in the literature for solving optimization problems. Tree-seed algorithm (TSA) is inspired from relation between trees and seeds that a population-based evolutionary algorithm. when create process of a seed occur in TSA, the position updating of each dimension of the seed is calculated separately. In scope this study, Some changes have been implemented to original TSA. A new operator was added to the position update equation of original TSA when create a seed from tree. This operator is calculated by dynamically according to the dimension of the problem. As the dimension of the problem increases, the value of the this operator decreases. In addition, we determined an upper and a lower bound for the update process of the seed. The Improved Tree Seed Algorithm (ITSA) proposed in this study and the TSA have been tested on some benchmark functions in the literature. As a result, when the experimental results are taken into consideration, it is understood that the proposed algorithm ITSA is obtained more effective results for benchmark functions than TSA. Moreover, it is observed that ITSA found quite successful results compared with TSA for large-scale benchmark problems. © 2018 International Association of Computer Science and Information Technology.Öğe A new hybrid heuristic approach for solving green traveling salesman problem(2011) Özceylan E.; Kiran M.S.; Atasagun Y.This study presents a novel problem called green travelling salesman problem (GTSP), an extension of the classical travelling salesman problem (TSP). Proposed GTSP considers not just for the route distance, also accounts emitted CO2, consumed fuel, travelling times/speed and their costs with a more comprehensive objective function. The aim of this study is to shed light on the trade-offs between various objectives and offers managerial insights on decisions in a green frame of TSP. Therefore, a nonlinear mixed integer mathematical model is proposed for the GTSP and computational experiments are performed on generated hypothetical instances to obtain optimal solutions through Lingo 11.0. Due to more NP-hard nature of GTSP contrary to the TSP, a hybrid approach contains ant colony optimization (ACO) and artificial bee colony (ABC) methods is designed to solve test problems from the small size for accuracy to the large scale for efficiency and the results are compared to the solutions gained by solving the same problems by Lingo 11.0. The numerical results show that hybrid approach is more applicable and effective than Lingo 11.0 in reasonable time.Öğe Prediction of football match outcomes based on bookmaker odds by using k-nearest neighbor algorithm(International Association of Computer Science and Information Technology, 2018) Esme E.; Kiran M.S.Making predictions for the sport competitions, which are followed by wide masses, has always been an interesting field for sport fans, bettors, researchers and etc. despite the complexity and uncertainty of many factors. The result of a sport competition is affected by many independent variables and factors. The number of the variables that are included in the calculation affects the accuracy of the prediction. It is difficult for an ordinary punter to cope with these factors that are in high numbers and that have a high complexity. On the other hand, a bookmaker must consider all the factors that might affect the result. When a bookmaker determines the odds with some delicate calculations, it is actually digitizing all the above-mentioned complex factors. In this way, the consistency of the betting odds of past competitions becomes a good indicator to be able to make predictions. In this study, a prediction model has been suggested for football game, which is more common than the other sports branches. In this model, the basic design approach is to measure the similarity between competitions in a way based on betting odds. The model was enhanced with the performance data obtained by the past games. Adding the risk analysis option to the model decreased the margin of error in games predicted at a great deal. The Super League of Turkey competitions were used to test the model in which the k-Nearest Neighbor Algorithm was preferred as the estimation technique. © 2018 International Association of Computer Science and Information Technology.Öğe Two dimensional cuckoo search optimization algorithm based despeckling filter for the real ultrasound images(Springer Verlag, 2018) Gupta P.K.; Lal S.; Kiran M.S.; Husain F.A clinical ultrasound imaging plays a significant role in the proper diagnosis of patients because, it is a cost-effective and non-invasive technique in comparison with other methods. The speckle noise contamination caused by ultrasound images during the acquisition process degrades its visual quality, which makes the diagnosis task difficult for physicians. Hence, to improve their visual quality, despeckling filters are commonly used for processing of such images. However, several disadvantages of existing despeckling filters discourage the use of existing despeckling filters to reduce the effect of speckle noise. In this paper, two dimensional cuckoo search optimization algorithm based despeckling filter is proposed for avoiding limitations of various existing despeckling filters. Proposed despeckling filter is developed by combining fast non-local means filter and 2D finite impulse response (FIR) filter with cuckoo search optimization algorithm. In the proposed despeckling filter, the coefficients of 2D FIR filter are optimized by using the cuckoo search optimization algorithm. The quantitative results comparison between the proposed despeckling filter and other existing despeckling filters are analyzed by evaluating PSNR, MSE, MAE, and SSIM values for different real ultrasound images. Results reveal that the visual quality obtained by the proposed despeckling filter is better than other existing despeckling filters. The numerical results also reveal that the proposed despeckling filter is highly effective for despeckling the clinical ultrasound images. © 2018 Springer-Verlag GmbH Germany, part of Springer Nature