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Articles 1 - 6 of 6
Full-Text Articles in Physical Sciences and Mathematics
Binary Text Classification Using Genetic Programming With Crossover-Based Oversampling For Imbalanced Datasets, Mona Aljero, Nazi̇fe Di̇mi̇li̇ler
Binary Text Classification Using Genetic Programming With Crossover-Based Oversampling For Imbalanced Datasets, Mona Aljero, Nazi̇fe Di̇mi̇li̇ler
Turkish Journal of Electrical Engineering and Computer Sciences
It is well known that classifiers trained using imbalanced datasets usually have a bias toward the majority class. In this context, classification models can present a high classification performance overall and for the majority class, even when the performance for the minority class is significantly lower. This paper presents a genetic programming (GP) model with a crossover-based oversampling technique for oversampling the imbalanced dataset for binary text classification. The aim of this study is to apply an oversampling technique to solve the imbalanced issue and improve the performance of the GP model that employed the proposed technique. The proposed technique …
An Evolutionary-Based Image Classification Approach Through Facial Attributes, Seli̇m Yilmaz, Cemi̇l Zalluhoğlu
An Evolutionary-Based Image Classification Approach Through Facial Attributes, Seli̇m Yilmaz, Cemi̇l Zalluhoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
With the recent developments in technology, there has been a significant increase in the studies on analysisof human faces. Through automatic analysis of faces, it is possible to know the gender, emotional state, and even theidentity of people from an image. Of them, identity or face recognition has became the most important task whichhas been studied for a long time now as it is crucial to take measurements for public security, credit card verification,criminal identification, and the like. In this study, we have proposed an evolutionary-based framework that relies ongenetic programming algorithm to evolve a binary- and multilabel image classifier …
Genetic Programming-Based Pseudorandom Number Generator For Wireless Identification And Sensing Platform, Cem Kösemen, Gökhan Dalkiliç, Ömer Aydin
Genetic Programming-Based Pseudorandom Number Generator For Wireless Identification And Sensing Platform, Cem Kösemen, Gökhan Dalkiliç, Ömer Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
The need for security in lightweight devices such as radio frequency identification tags is increasing and a pseudorandom number generator (PRNG) constitutes an essential part of the authentication protocols that provide security. The main aim of this research is to produce a lightweight PRNG for cryptographic applications in wireless identification and sensing platform family devices, and other related lightweight devices. This PRNG is produced with genetic programming methods using entropy calculation as the fitness function, and it is tested with the NIST statistical test suite. Moreover, it satisfies the requirements of the EPCGen2 standards.
Speciation-Based Genetic Algorithm In Analog Circuit Design, Hasari̇ Karci̇, Gülay Tohumoğlu, Ari̇f Nacaroğlu
Speciation-Based Genetic Algorithm In Analog Circuit Design, Hasari̇ Karci̇, Gülay Tohumoğlu, Ari̇f Nacaroğlu
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a speciation procedure that improves the local search capability of the genetic algorithm in analog circuit design. There is no need for additional circuit simulation in order to apply this procedure. The procedure is tested in Gaussian, sigmoid, cube, and square circuit design problems. Two sets of 125 simulations with the same seed values are performed for each problem using both the proposed procedure and the canonical genetic algorithm. The simulation results show that the method is statistically better than the canonical genetic algorithm, which suffers from bad locality. The effects of the population size and speciation …
Symbolic Regression Of Crop Pest Forecasting Using Genetic Programming, Basim Alhadidi, Alaa Alafeef, Heba Al-Hiari
Symbolic Regression Of Crop Pest Forecasting Using Genetic Programming, Basim Alhadidi, Alaa Alafeef, Heba Al-Hiari
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose and evaluate a mathematical model that describes the reported data on crop pests to get an accurate prediction of production costs, food safety, and the protection of the environment. Meteorological factors are not the only things that affect a bumper harvest; it is also affected by crop plant diseases and insect pests. Studies show that relying solely on the naked-eye observations of experts to forecast well-planned agriculture is not always sufficient to achieve effective control. Providing fast, automatic, cheap, and accurate artificial intelligence-based solutions for that task can be of great realistic significance. The proposed …
Meta-Genetic Programming: Co-Evolving The Operators Of Variation, Bruce Edmonds
Meta-Genetic Programming: Co-Evolving The Operators Of Variation, Bruce Edmonds
Turkish Journal of Electrical Engineering and Computer Sciences
The standard Genetic Programming approach is augmented by co-evolving the genetic operators. To do this the operators are coded as trees of indefinite length. In order for this technique to work, the language that the operators are defined in must be such that it preserves the variation in the base population. This technique can varied by adding further populations of operators and changing which populations act as operators for others, including itself, thus to provide a framework for a whole set of augmented GP techniques. The technique is tested on the parity problem. The pros and cons of the technique …