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https://hdl.handle.net/20.500.12587/8389

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Time-Invariant and Localized Secure Reception With Sequential Multicarrier Receive-FDA
(IEEE-Inst Electrical Electronics Engineers Inc, 2023) Akkoç, Ahmet; Korkmaz, Nilay Aytas; Genç, Yasin; Afacan, Erkan; Yazgan, Erdem
Secure communication in the physical layer (PHY) using frequency diverse array (FDA) antennas has become a prominent research topic in recent years due to the unique range-;angle-dependent beam pattern exhibited by FDAs. However, the time-varying and periodic nature of the FDA beam pattern prevents the achievement of a time-invariant range-angle-focused beam pattern. Consequently, a range-angle-focused beam is only achieved at a specific time instant. Therefore, it is not yet possible to focus a beam on a specific point or area in space permanently in a time-invariant manner, due to both natural propagation mechanisms and the independent time parameter. Once a wave is transmitted, time variation cannot be altered. Thus, for the FDA beam pattern, it continues to propagate over time indefinitely. However, in the case of receiving, the time parameter is under the control of the receiver. The receiver can set the time at which the incoming wave is sampled or acquired. In this study, a cross-linear array structure called the sequential multicarrier receive FDA (SMCR-FDA) and a relevant methodology are proposed to obtain a three-dimensionally localized time-invariant range-angle-focused receive beam pattern. Additionally, several novel concepts, including the cross-linear array structure, the secure reception concept, and the positional modulation (PoM) technique, are introduced.
The effect of sintering parameters and MgO ratio on structural properties in Al7075/MgO composites: a review
(Springer, 2023) Pul, Muharrem; Erdem, Ümit; Türköz, Mustafa Burak; Yıldırım, Gürcan
In this experimental study, Al7075 matrix composites reinforced with different proportions of MgO were produced by powder metallurgy method. Different sintering temperatures and times were applied in the powder metallurgy production process. In the second stage of the experimental study, firstly, the porosity and hardness measurements of the composite materials were made. Then, microstructure images were taken with SEM and optical microscope, and XRD analyzes were performed. Using the obtained data, the effects of different MgO ratios and different sintering parameters on the structural properties of composite materials were evaluated. As the sintering temperature increased, the density of the composite structure increased and then decreased again. Accordingly, the amount of porosity first decreased and then increased again. Significant size growth occurred in all samples sintered at 600 degrees C. This change was associated with the high amount of porosity in the same samples. A more stable microstructure was obtained from the samples sintered at 550 degrees C. Thus, it can be said that the presence of excess MgO particles in the system causes the material quality to deteriorate due to increased microscopic structural problems, wetting rates, intergranular interaction problems between adjacent layers, recovery mechanism and entanglement of voids, and dislocations. Therefore, the ideal rate, time and temperature value for MgO addition should be carefully determined. As a result, it was seen that the sintering temperature of 550 degrees C gave the most suitable results. The sintering time strengthened the phase volume of the Al7075 alloy, making the compound more stable.
Stationary Aircraft Detection From Satellite Images
(Istanbul Univ, Fac Engineering, 2012) Polat, Ediz; Yıldız, Cihat
Satellite image analysis is an important research area in the field of image processing. Detection and recognition of regions and objects from satellite images find many useful civil applications such as detection of buildings, roads, bridges and other man-made objects as well as land plant classification. On the other hand, the detection of stationary aircrafts in airports can be strategically important in military applications. In this study, a learning-based system that detects stationary aircrafts in satellite images obtained from Google Earth is developed. The features that emphasize the geometric structure of an aircraft are determined using 2D Gabor filter. The aircraft detection is performed using Support Vector Machines (SVM) classification method. The SVM is a supervised learning method that analyzes data and recognizes patterns for classification The SVM takes a set of input data (a vector consists of Gabor filter output of images) and predicts the one of two classes (aircraft or non-aircraft). The performance of the system is demonstrated using satellite images collected from airports in Europe and United States.
Spatial light modulator design and generation of structured electromagnetic waves using digital light processors
(Wroclaw Univ Science Technology, 2022) Yalçınkaya, F.; Koç, Tarık; Pala, Zeydin
Spatial light modulators (SLMs) are versatile devices used for optical studies. These instruments have a wide area of application in photonics. Additionally, SLMs have potential utility in different applications, such as biomedical applications, laser based surgery for precise cutting and as optical tweezers to separate cells in a petri container. However, the high cost of SLM devices prevents their widespread use in many areas, including industrial areas and scientific research laboratories. This paper demonstrates how to design a digital light processor (DLP) based low-cost SLM and describes how to obtain structured electromagnetic waves with the designed SLM. Therefore, this research was undertaken to design and produce a low-cost SLM device for optical applications. For this purpose, two prerequisites had to be fulfilled, the first was to use suitable components of a projection device with DLP-based digital micro-mirror device (DMD), and the second was to eliminate unnecessary SLM components from the system. Finally, holographic images reflected on the SLM screen were created by using Mathematica software program to change the amplitude and phase of the electromagnetic waves in order to obtain the structured electromagnetic waves.
Sliding Mode Control-Based MPPT and Output Voltage Regulation of a Stand-alone PV System
(Sciendo, 2022) Manuel, Nelson Luis; İnanç, Nihat
When it comes to reducing emissions caused by the generation of electricity, among different renewable energy sources, the solar energy gains prominence, due to its geographical availability, simplicity of implementation, and absence of physical moving parts. However, the performance of photovoltaic systems is dependent on environmental conditions. Depending on temperature and solar irradiation, the photovoltaic (PV) system has an operating point where maximum power can be generated. The techniques that are implemented to find this operating point are the so-called maximum power point tracking (MPPT) algorithms. Since weather conditions are variable in nature, the output voltage of the PV system needs to be regulated to remain equal to the reference. Most of the existing studies focus either on MPPT or on voltage regulation of the PV system. In this paper, the two-stage PV system is implemented so that both MPPT and voltage regulation are achieved simultaneously. Additionally, an improved version of the perturb and observe (P&O) algorithm based on artificial potential fields (APF), called APF-P&O, is presented. According to the results of the simulations carried out in MATLAB/Simulink software, the APF-P&O method is more efficient than the conventional method.
Sensorless Vector Control for Induction Motor Drive at Very Low and Zero Speeds Based on an Adaptive-Gain Super-Twisting Sliding Mode Observer
(IEEE-Inst Electrical Electronics Engineers Inc, 2023) Nurettin, Abdulhamit; İnanç, Nihat
To achieve a balance between estimation accuracy and the chattering problem for sensorless induction motor IM drive systems at very low and zero speeds, an adaptive-gain super-twisting sliding mode observer (AGSTSMO) is proposed. The value of the adaptive gains (experimental observer coefficients) in the control law is assigned utilizing Lyapunov stability theory to ensure expeditious convergence of the estimated variables to improve the accuracy and suppress chattering at very low and zero speeds operation. The AGSTSMO eliminates the need to use a low-pass filter to obtain the equivalent control, as in the traditional first-order sliding-mode observer, which causes a delay in estimating the equivalent control law. Simulation and experimental results are shown under different operating conditions to illustrate the effectiveness of the suggested approach, which achieves excellent estimation precision and chattering elimination capability simultaneously, thus increasing robustness versus deviations of the motor parameters. Moreover, to prove the superiority and efficiency of the proposed observer is compared to that of a super-twisting sliding mode observer (STSMO) under various operating conditions.
Risk-based Optimal Bidding and Operational Scheduling of a Virtual Power Plant Considering Battery Degradation Cost and Emission
(Univ Suceava, Fac Electrical Eng, 2023) Akkaş, Özge Pınar; Çam, Ertuğrul
A virtual power plant (VPP) is a system combining various types of distributed energy resources (DERs) to provide a reliable power system operation. It provides the advantage of making changes in generation according to variety, price, and demand conditions with bringing renewable energy sources (RES) in a single portfolio and using their flexibility. In this study, it is tried to find optimal bidding and operational scheduling of a VPP containing Wind Power Plant (WPP), Photovoltaic Power Plant (PVPP), Heat-Only Unit (HOU), Battery Energy Storage System (BESS), Combined Heat and Power Plant (CHPP), and electrical/thermal demands and participating in the day-ahead electricity market in 24-h time interval. It is aimed to maximize profit and minimize emissions with considering the battery cost. A stochastic model is formed by considering the uncertainty arising from RES. In addition, CVaR (Conditional Value at Risk) as a risk measurement technique is applied against the risk arising from low profit scenarios. The proposed optimization problem formulated as a stochastic Mixed Integer Nonlinear Programming (MINLP) model and is solved by solver LINDO in GAMS (General Algebraic Modelling System). The case studies are implemented to show the applicability and effectiveness of the presented model.
Optimization of indoor thermal comfort values with fuzzy logic and genetic algorithm
(Ios Press, 2023) Balci, Sonay Görgülü; Ersöz, Süleyman; Lüy, Murat; Türker, Ahmet Kürşad; Barışçı, Necaattin
It is known that in crowded environments such as educational institutions and workplaces, keeping indoor air quality and climate within certain limits contributes to success and production. For this purpose, a system has been developed to ensure air quality well-being in working environments. In our study, the Arduino processor managed by the fuzzy logic control system (FLC) starts to work with the trigger of the motion sensor HC-SR501. The inputs of the FLC system are defined as LM-35 sensor for temperature, DHT-11 for humidity, MQ-135 for air quality, MQ-9 sensor for CO and explosive gas. The designed system evaluates the instantaneous data obtained from the fuzzy logic system rule base and decides which of the output air filter, heater and alarm systems will operate at what speed. In order to increase system efficiency, fuzzy logic input membership values are optimized by genetic algorithm.
BLOCKBOX: Blockchain based black box designing and modeling
(Wiley, 2024) Korkuç, Çağatay; Korkmaz, Nilay Aytas; Genç, Yasin; Akkoc, Ahmet; Afacan, Erkan; Yazgan, Erdem
With the development of technology, data has become more accessible. The storage of critical and valuable information is getting harder and harder with the increase of cyber attacks and vulnerabilities of network and internet. The centralized storage of data causes security and privacy problems. As a remedy to these problems, blockchain has occurred. The reliability, transparency, integrity and confidentiality of the data have been increased with the blockchain technology. Blockchain maintains the immutability of the data with cryptographic hash algorithms. The data is kept in distributed structures with the consensus algorithms so that it is not lost. Projects and studies using blockchain technology have shown that data stored in centralized structures is not as reliable as data that is distributed and secured by cryptographic algorithms, smart contracts, and consensus. The data of flights, which is a critical data, has a great place in world transportation. The parameters inside the black boxes guide us on why the aircrafts have crashed: whether the responsibility belongs to the manufacturer, to the pilot, or to the aircraft technicians. In this way, the real reasons of the accident may be determined and measures can be taken for the accidents that may occur afterwards. In addition, the safe delivery of all black box data to the interested parties and its storage in a way that is immutable will not only benefit to the manufacturer's self-development by processing the data, but also help flight companies to find optimum flight data. Both the flight companies and the manufacturer will be able to read the black box data, thus the suspicion of data manipulation will be eliminated and the data will become more transparent. In this study, a system is proposed in which an aircraft's black box data can be saved safely and securely with the help of blockchain technology.
Advanced forecast models for the climate and energy crisis: The case of the California independent system operator
(Pergamon-Elsevier Science Ltd, 2025) Bulut, Merve; Aydilek, Hüseyin; Erten, Mustafa Yasin; Özcan, Evrencan
Climate change across the globe, especially extreme temperature events, is increasing pressures on energy systems. The extraordinary situation that California and the West faced in late August and early September 2022, when record temperatures led to a spike in electricity demand, provided an important backdrop for the resilience and sustainability of clean energy technologies. The electricity market managed by the California Independent System Operator is considered in this study to examine the potential impacts on electricity demand spikes and system resilience. The methodology of the research involves analyzing the system operator's responses to electricity demand using advanced deep learning algorithms, convolutional neural network - long-short term memory and attention mechanism models. 1, 3 and 7-days forecasts of electricity demand were made using models in the day ahead market. In 1-day forecasts, while the former models have a mean absolute percentage error value of 12.40%, the latter model has a lower error rate of 10.36%. Overall findings obtained from various scenarios show that the long-short term memory - attention mechanism can more effectively understand complex patterns in energy demand and has the potential to increase system stability against such extreme weather events. The advanced horizon of the study offers an important perspective on how clean energy technologies, especially battery energy storage systems, can provide solutions to today's priority problems such as climate change and extreme temperature.
A Novel Identity-Based Privacy-Preserving Anonymous Authentication Scheme for Vehicle- to-Vehicle Communication
(Kaunas Univ Technology, 2023) Genç, Yasin; Korkuç, Çağatay; Aytaş, Nilay; Afacan, Erkan; Sazlı, Murat H.; Yazgan, Erdem
This paper proposes a novel bilinear pairing-free identity-based privacy-preserving anonymous authentication scheme for vehicle-to-vehicle (V2V) communication, called NIBPA. Today, vehicular ad hoc networks (VANETs) offer important solutions for traffic safety and efficiency. However, VANETs are vulnerable to cyberattacks due to their use of wireless communication. Therefore, authentication schemes are used to solve security and privacy issues in VANETs. The NIBPA satisfies the security and privacy requirements and is robust to cyberattacks. It is also a pairing-free elliptic curve cryptography (ECC)-based lightweight authentication scheme. The bilinear pairing operation and the map-to-point hash function in cryptography have not been used because of their high computational costs. Moreover, it provides batch message verification to improve VANETs performance. The NIBPA is compared to existing schemes in terms of computational cost and communication cost. It is also a test for security in the random oracle model (ROM). As a result of security and performance analysis, NIBPA gives better results compared to existing schemes.
A Novel Approach for Channel Allocation In OFDM Based Cognitive Radio Technology
(Springer, 2021) Yılmazel, Rüstem; İnanç, Nihat
When the number of users in the radio environment is increasing and the rapid development in the wireless environment is examined, the efficient use of the spectrum decreases gradually. Cognitive radio technology as one of the spectrum sensing techniques for 5G (Fifth Generation) and beyond communication systems has been studied in recent years to prevent spectrum inefficiency. According to different researches, spectrum usage is not always the same by the licensed user. Certain parts of the spectrum is used very little or inefficient. OFDM-based cognitive radio technology developed to increase spectum efficiency has enabled the use of empty channels. In this article, a new approach is proposed by combining artificial intelligence techniques and spectrum detection algorithms. The accuracy of the results was observed by applying this new technique to OFDM technology. Genetic algorithm (GA) is used to make the best field channel allocation and highest accuracy for the use of the spectrum. It was found that the optimized result with the help of genetic algorithm was better than the results without using genetic algorithm. As a result of the study, the accuracy of the channel allocation has increased significantly with the new approach proposed. In this article, it is possible to integrate different spectrum allocation techniques for secondary users by using artificial intelligence. The requirements of the system are given as input data and accordingly the probability of detection is examined. Thanks to this method, empty frequencies are continuously scanned and correct channel allocation is ensured. The results obtained in this article show that both the channel assignment is correct and the primary user is detected without any problems.
A novel hybrid global optimization algorithm having training strategy: hybrid Taguchi-vortex search algorithm
(Tubitak Scientific & Technological Research Council Turkey, 2021) Saka, Mustafa; Çoban, Melih; Eke, İbrahim; Tezcan, Süleyman Sungur; Taplamacıoğlu, Müslüm Cengiz
In this paper, a novel hybrid Taguchi-vortex search algorithm (HTVS) is proposed for solving global optimization problems. Taguchi orthogonal approximation and vortex search algorithm (VS) are hybridized in presenting method. In HTVS, orthogonal arrays in the Taguchi method are trained and obtained better solutions are used to find global optima in VS. Thus, HTVS has better relation between exploration and exploitation, and it exhibits more powerful approximation to find global optimum value. Proposed HTVS algorithm is applied to sixteen well-known benchmark optimization test functions with different dimensions. The results are compared with the Taguchi orthogonal array approximation (TOAA), vortex search algorithm, grey wolf optimizer (GWO), sine cosine algorithm (SCA), moth-flame optimization algorithm (MFO), whale optimization algorithm (WOA) and salp swarm algorithm (SSA). In order to compare the effectiveness of HTVS statistically, Wilcoxon signed-rank test (WSRT) is used in this study. Furthermore, HTVS is applied to two different real engineering problems having some constraints (tension/compression spring design and pressure vessel design). All obtained results suggested that HTVS can find optimal or very close to optimal results. Moreover, it has good computational ability and fast convergence behavior as well.
Optimizing Energy Hub System Operation With Electrical And Thermal Demand Response Programs
(Konya Teknik Univ, 2024) Akkaş, Özge Pınar; Yıldız, Yağmur Arıkan
Electricity consumption is increasing rapidly and many countries are looking for ways to cope with the energy crisis. Morever, the world is facing the problem of global warming caused by emissions. Therefore, it is of great importance to operate power systems efficiently. Energy Hub (EH) represents a versatile energy system capable of providing efficient and optimal solutions for the operation of power systems across multiple carriers. This paper examines the optimization of an EH encompassing renewable energy systems (RES) like wind and photovoltaic, combined heat and power (CHP), transformer, absorption chiller, energy storage system (ESS) and furnace with aiming at minimizing the cost. Demand response is an energy sector strategy that entails modifying electricity consumption patterns in reaction to fluctuations in electricity supply or pricing. The objective of demand response programs (DRP) is to curtail or shift electricity consumption during periods of elevated electricity prices. Therefore, Electrical Demand Response Program (EDRP) for electrical demand and the Thermal Demand Response Program (TDRP) for heating demand are incorporated into the EH. The optimization problem is formulated as Mixed Integer Linear Programming (MILP) and solved with CPLEX solver in GAMS. The outcomes of various case studies are compared to ascertain the model's efficiency.
Inserting of heuristic techniques into the stability regions for multiarea load frequency control systems with time delays
(Tubitak Scientific & Technological Research Council Turkey, 2022) Saka, Mustafa; Sönmez, Şahin; Eke, İbrahim; Gözde, Haluk; Taplamacıoğlu, Müslüm Cengiz; Ayasun, Saffet
The design and optimization of robust controller parameters are required to improve the controller perfor-mances and to keep the stability of load frequency control (LFC) system. In addition, reducing the number of iterations and computational time is very important for swiftly tuning of the controller parameters and the system to reach stability rapidly. For this purpose, this study presents the inserting of heuristic optimization techniques into stability regions method identified in proportional-integral (PI) controllers space for multiarea LFC systems with communication time delays (CTDs). This method consists of two steps: determination of stability region for the system and application of heuristics. Stability region for the system is found via stability boundary locus (SBL) and moth-flame optimization (MFO), particle swarm optimization (PSO), sine cosine algorithm (SCA), slime mould algorithm (SMA) and whale optimization algorithm (WOA) are inserted and applied to this region. In addition, a cost function having time domain specifications is developed for improving the performances of LFC and it is compared with the well-known integral error functions. Also, the robust stability region, which tolerates any system parameter and any time delay variation, is identified and the significance of this region is given for robustness analysis. It is observed from the analyses that better system outputs have been obtained with developed cost function. Steady state errors are minimized and transient state performances are improved with the proposed method. Moreover, desired system performances have been achieved with lower computational time and iteration number (approximately more than about 89% reduced according to classical approach) without deteriorating the stable structure of the system by the proposed method.
Yüz ifade analizinde öznitelik seçimi ve çoklu SVM sınıflandırıcılarına etkisi
(2009) Güneş, Turan; Polat, Ediz
Yüz ifadeleri, insan ilişkilerinde anlam bütünlüğünün sağlanması için büyük rol oynayan, sözlü olmayan işaretlerdir. İnsanoğlu yüz ifadelerini kavramada herhangi bir zorluk çekmezken, bu durum makineler için geçerli olmayıp, halen güvenilir ifade tanıma sistemleri üzerinde araştırmalar yapılmaktadır. Bu çalışmada, insanın içinde bulunabileceği 7 ifade durumunun (öfke, iğrenme, korku, mutluluk, ifadesizlik, üzüntü ve şaşkınlık) analizi gerçekleştirilmiştir. Bu amaçla, her bir ifade için alınan sabit görüntülerin öznitelikleri Gabor filtreleri kullanılarak çıkartılmış ve farklı öznitelik seçme algoritmaları kullanılarak ifadeleri temsil eden en iyi öznitelik kümeleri oluşturulmuştur. Seçilen öznitelik kümelerinin çoklu SVM (Support Vector Machines-Destek Vektör Makineleri) sınıflandırıcıları üzerindeki etkileri incelenmiş ve sınıflandırma doğruluklarının kullanılan öznitelik seçme algoritmalarına göre nasıl değiştiği karşılaştırmalı olarak değerlendirilmiştir. Çoklu sınıflandırma yapılması amacıyla SVM, One-Vs-One, One-Vs-Rest ve MC-SVM olmak üzere 3 farklı yaklaşım ile birlikte kullanılmıştır. Ayrıca öznitelik seçimi yapılmadan alınan sınıflandırma başarım sonuçları da incelendiğinde, öznitelik seçiminin sınıflandırma doğruluğunun artması yönünde genel olarak büyük etkisinin olduğu görülmüştür.
A Study of Energy Efficiency in Rail Vehicles
(2020) Arıkan, Yağmur; Şen, Tolga Altuğ; Çam, Ertuğrul
Today, rail vehicles are frequently preferred both in urban and intercity transportation due to their high passenger capacity, speed and increasing environmental awareness. As in every field, energy efficiency studies have become compulsory in these vehicles. Because, they have high energy consumption even in their daily services. For energy efficiency, there are various strategies such as electrification losses reduction, utilization of regenerative braking and improvement of comfort function and efficient driving techniques have been performed in this paper. For this purpose, firstly, the driving of a rail vehicle has been modeled on Matlab considering all vehicle information, track information and operational constraints. Then, four different driving styles have been determined for the efficient use of energy and their effects on travel time and energy consumption have been examined. The study has been tested with the practical data of Ankaray metro line which has eleven stations and is 8.527 km long. According to the results of the paper, coasting control is more effective for long distances and reduction of the maximum speed is more convenient for short distances. Furthermore, it has been demonstrated that thanks to the determined strategies, the vehicle can save up to 11.54-36.37% energy compared to practical driving.
Analysis of the Studies on E-learning Acceptance of Learners in the Middle East and the Proposal of an Extended Technology Acceptance Model
(2020) Baki, Rahmi; Birgören, Burak
E-learning applications can result in various expectations, attitudes and needs based on the users’ geographical regions and cultural roots, therefore, design of e-learning systems by taking into account the individuals’ cultural and demographic attributes is crucial for an effective learning environment. This study considers 44 researches that assess users’ e-learning acceptance characteristics in 10 different Middle Eastern countries, where 45 external variables are proposed as predeterminants of Perceived Usefulness (PU) and Perceived Ease of Use (PEOU), both of which are Technology Acceptance Model’s (TAM) belief components. 75 hypotheses are tested 155 times where these external variables are presented to be the antecedents of the belief components. With the help of a region-based literature review; it is aimed to identify the factors causing users’ system acceptance in the Middle East. As a result, an extended TAM is proposed for the Middle East by incorporating the most frequently accepted hypotheses into the original TAM.
Ateş böceği algoritması kullanarak MC-CDMA sistemlerinde çevrimsel ön takı uzunluğunun belirlenmesi
(2017) Seyman, Muhammet Nuri
Çok taşıyıcılı kod bölmeli çoklu erişim gibi yüksek hızlarda veri iletimini sağlayan çok taşıyıcılı haberleşme sistemlerinde semboller arası girişim ve kanallar arası girişimi önlemek için çevrimsel ön takıdan faydalanılır. Bu yüzden çevrimsel ön takı uzunluğunun uygun bir şekilde belirlenmesi, sadece hata performansını artırmayacak aynı zamanda da sembol enerjisindeki azaltmaları da engelleyecektir. Bu çalışmada çevrimsel ön takı uzunluklarının belirlenmesi için yeni bir meta-sezgisel algoritma olan ateş böceği algoritması önerilmiştir. Önerilen bu algoritmayı kullanarak, Genetik Algoritmalar ve 1/8 oranlı çevrimsel ön takı kod uzunluklu sistemlere göre daha iyi bit hata oranları elde edilmiştir. Parametre sayısının az ve performansının Genetik Algoritmalara göre yüksek olması nedeniyle bu algoritma çok taşıyıcılı kod bölmeli çoklu erişim sistemlerinde çevrimsel ön takı boyutlarının adaptif olarak belirlenmesinde kullanılabilir
Filled fonksiyon kullanarak vana etkili ekonomik yük dağıtımı probleminin çözülmesi
(2017) Eke, İbrahim; Tezcan, Süleyman Sungur; Çelik, Coşkun
Bu makalede, ekonomik yük dağıtımı problemine filled fonksiyonu metodu uygulanmıştır. Vana etkisi gibidoğrusal olmayan durumlar içeren ekonomik yük dağıtımı probleminin çözümünde önerilen methodunbaşarısı gösterilmiştir. Eşitlik ve eşitsizlik içeren üç farklı test durumunda, önerilen metot test edilerekdoğrulanmıştır. Elde edilen benzetim sonuçlarına göre; filled fonksiyon metodu, parametrelerin ilkdeğerlerine daha az bağlıdır ve geliştirilen diğer algoritmalara göre daha verimli çalışmaktadır. Bunlara ilavaten, büyük güç sistemlerinde önerilen algoritmanın kolaylıkla uygulanabileceği öngörülmektedir.

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