Soil Classification deals with the systematic categorization of soils based on distinguished characteristics as well as criteria. We developed Data Mining techniques like: GATree, Fuzzy Classification rules and Fuzzy C Means algorithm for classifying soil texture in agriculture soil data. In this paper, we give a comparative study of developed algorithms. The study is used to compare and analyz...

Medical image fusion has been used to derive the useful complimentary information from multimodal images. The prior step of fusion is registration or proper alignment of test images for accurate extraction of detail information. For this purpose, the images to be fused are geometrically aligned using mutual information (MI) as similarity measuring metric followed by genetic algorithm to maximiz...

Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some kinds...

Clustering method, which groups thousands of genes by their similarities of expression levels, has been used for identifying unknown functions of genes. Fuzzy clustering method that is one category of clustering assigns one sample to multiple groups according to their membership degrees. It is more appropriate than hard clustering algorithms for analyzing gene expression profiles since single g...

A type-2 Takagi-Sugeno-Kang fuzzy neural system is proposed and its parameter update rules are derived using fuzzy clustering and gradient learning algorithms. The proposed type-2 fuzzy neural system is used for the control and the identification of a real-time servo system. Fuzzy c-means clustering algorithm is used to determine the initial places of the membership functions to ensure that the...

The Chiu’s method which generates a Takagi-Sugeno Fuzzy Inference System (FIS) is a method of fuzzy rules extraction. The rules output is a linear function of inputs. In addition, these rules are not explicit for the expert. In this paper, we develop a method which generates Mamdani FIS, where the rules output is fuzzy. The method proceeds in two steps: first, it uses the subtractive clustering...

The Markov Weighted Fuzzy Time Series (MWFTS) is a method for making predictions based on developing fuzzy time series (FTS) algorithm. MWTS has overcome certain limitations of FTS, such as repetition logic relationships and weight considerations relationships. main challenge the MWFTS absence standardized rules determining partition intervals. This study compares model to methods Genetic Algor...

Due to the unique characteristics such as handling complex, nonlinear, and sometimes intangible dynamic systems, fuzzy systems are used in the modeling of InputOutput data of the process. The combination of fuzzy rule-based systems with genetic algorithms can lead to very useful descriptions of several optimization and search problems. In this paper, clustering strategy is implemented in the de...

Due to the unique characteristics such as handling complex, nonlinear, and sometimes intangible dynamic systems, fuzzy systems are used in the modeling of InputOutput data of the process. The combination of fuzzy rule-based systems with genetic algorithms can lead to very useful descriptions of several optimization and search problems. In this paper, clustering strategy is implemented in the de...

clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. k-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. in recent years, several algorithms are provided based on evolutionary algorithms for cluster...