The main problem in design fuzzy models is to identify their structure. This means recognise the variables that better characterise the system dynamics, the number of membership functions partitioning each variable, as well as their distribution and fuzziness degree. This work presents two pre-processing methods for structure identification of fuzzy models. The first approach uses the statistic...

in modern agriculture, image processing technique is used for mechanization and intelligent machines instead of humans. one of them is identifying varieties of plants and fruits. identifying plant varieties is important in plant eugenic programs. visual examination of plant leaves and fruits are the common processes for this aim. identification and classification of plants using machine vision ...

Delay-partitioning approach to stability criteria for T-S fuzzy systems with time-varying delay Fuping Zhou1 and Jun Yang2 1 School of Civil Engineering and Architechture, Southwest University of Science and Technology, Mianyang, Sichuan, 621010, P.R. China, Email: zhoufp [email protected] 2College of Computer Science, Civil Aviation Flight University of China, Guanghan, Sichuan, 618307, P.R. China,...

In Power efficient routing for MANET is very crucial due to its dynamic topology, complexity and limited resources. The battery efficiency and power consumption of the selected routes play a vital role in the network lifetime. An optimum balance between these two constraints has to be made during route selection in order to obtain stable routes that would avoid network partitioning. In this pap...

In the past decade, various clustering algorithms based on the behaviour of real ants were proposed. The main advantage of these algorithms lies in the fact that no additional information, such as an initial partitioning of the data or the number of clusters, is needed. In this paper we show how the combination of the ant-based approach with fuzzy rules leads to an algorithm which is conceptual...

Data mining technology has emerged as a means for identifying patterns and trends from large quantities of data. Clustering is a primary data description method in data mining which group’s most similar data. The data clustering is an important problem in a wide variety of fields. Including data mining, pattern recognition, and bioinformatics. It aims to organize a collection of data items into...

in order to determine probable effects of sowing dates on partitioning coefficient of dry matter to different organs (leaf, stem and reproductive organs) in different wheat varieties (koohdasht, zagros and tajan) an experiment with crbd design and four replications was conducted. 5 sowing dates were included (29 december, 2007, 30 january, 2 march, 27 march, 1may, 2008). in order to quantify pa...

Route planning problems are among the activities that have the highest impact on logistical planning, transport and distribution because of their effects on efficiency in resource management, service levels, and client satisfaction. The difficulty of movement between different customers and other problems cause the uncertainty of time of movement. In this paper this uncertainty is presented by ...

In a fuzzy classifier with ellipsoidal regions, a fuzzy rule, which is based on the Mahalanobis distance, is defined for each class. Then the fuzzy rules are tuned so that the recognition rate of the training data is maximized. In most cases, one fuzzy rule per one class is enough to obtain high generalization ability. But in some cases, we need to partition the class data to define more than o...

This paper proposes a fuzzy partitioning subspace clustering algorithm that minimizes a variant of the FCM cost function with a weighted Euclidean distance and a penalty term. To this aim it considers the framework of proximal optimization. It establishes the expression of the proximal operator for the considered cost function and derives PFSCM, an algorithm combining proximal descent and alter...