Classification of Different Wheat Varieties by Using Data Mining Algorithms
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2016, Vol 4, Issue 2
Abstract
There are various applications using computer-aided quality controlling system. In this study, seed data set acquired from UCI machine learning database was used. The purpose of the study is to perform the operations for separation of seed species from each other in the seed data set. Three different seed whose data was acquired from the UCI machine learning database was used. Later it was classified by applying the methods of KNN, Naive Bayes, J48 and multilayer perceptron to the dataset. While wheat seed data received from the UCI machine learning database was classified, WEKA program was used. Depending on the number of neurons the highest classification success came in 7-layer neurons. Our success rate for the number of 7-layer neurons came to 97.17% When the classification success rate was calculated according to KNN for the values of different neighbour, the highest success rate for neighbour was set at 95.71% for 4. Neighbour. With this method, classification of seeds depending on their properties was provided more quickly and effectively.
Authors and Affiliations
Kadir Sabanci*| Karamanoglu Mehmetbey University, Faculty of Engineering Department of Electrical and Electronics Engineering, Karaman, Turkey, Mustafa Akkaya| KMU, Faculty of Engineering Department of Energy Systems Engineering, Karaman,Turkey
Keywords
Related Articles
- EP ID EP797
- DOI 10.18201/ijisae.62843
- Views 437
- Downloads 23
Avoiding Premature Convergence of Genetic Algorithm in Informational Retrieval Systems
Genetic algorithm is been adopted to implement information retrieval systems by many researchers to retrieve optimal document set based on user query. However, GA is been critiqued by premature convergence due to falling...
Rainfall estimation for the south shore of the Mediterranean Sea using MSG infrared images
The objective of this paper is the estimation of rainfall over the Algerian territory using MSG (Meteosat Second Generation) infrared data. To achieve this aim, we applied a calibrated GPI (GOES Precipitation Index) appr...
Particle Swarm Optimization Based Approach for Location Area Planning in Cellular Networks
Location area planning problem plays an important role in cellular networks because of the trade-off caused by paging and registration signalling (i.e., location update). Compromising between the location update and the...
Classification of Leaf Type Using Artificial Neural Networks
A number of shape features for automatic plant recognition based on digital image processing have been proposed by Pauwels et al. in 2009. Then Silva et al in 2014 have presented database comprises 40 diļ¬erent plant spec...
A Fuzzy Logic Controller with Tuning Output Scaling Factor for Induction Motor Control Taking Core Loss into Account
This paper presents a design of a fuzzy logic controller (FLC) with tuning output scaling factor for speed control of indirect field oriented induction motor (IM) taking core loss into account. The variation of output sc...