multi-path is favorite alternative for sensor networks, as it provides an easy mechanism to distributetraffic, as well as considerate fault tolerance. in this paper, a new clustering based multi path routingprotocol namely ecrr (energy efficient cluster based routing algorithm for improving reliability) isproposed, which is a new routing algorithm and guarantees the achievement to required qos ...

shear wave velocity (vs) data are key information for petrophysical, geophysical and geomechanical studies. although compressional wave velocity (vp) measurements exist in almost all wells, shear wave velocity is not recorded for most of elderly wells due to lack of technologic tools. furthermore, measurement of shear wave velocity is to some extent costly. this study proposes a novel methodolo...

Crime detection is one of the major issues in the field of criminology. In fact, criminology includes knowing the details of a crime and its intangible relations with the offender. In spite of the enormous amount of data on offenses and offenders, and the complex and intangible semantic relationships between this information, criminology has become one of the most important areas in the field o...

Fuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has been applied successfully in various fields including finance and marketing. Despite the successful applications, there are a number of issues that must be dealt with in practical applications of fuzzy clustering algorithms. This technical report proposes two extensions to the objective function based fuzzy...

Fuzzy clustering is well known as a robust and efficient way to reduce computation cost to obtain the better results. In the literature, many robust fuzzy clustering models have been presented such as Fuzzy C-Mean (FCM) and Possibilistic C-Mean (PCM), where these methods are Type-I Fuzzy clustering. Type-II Fuzzy sets, on the other hand, can provide better performance than Type-I Fuzzy sets, es...

Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...

identifying clusters or clustering is an important aspect of data analysis. it is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. it is a main task of exploratory data mining, and a common technique for statistical data analysis this paper proposed an improved version of k-means algorithm, namely persistent k...

Stochastic nature of earthquake has raised a challenge for engineers to choose which record for their analyses. Clustering is offered as a solution for such a data mining problem to automatically distinguish between ground motion records based on similarities in the corresponding seismic attributes. The present work formulates an optimization problem to seek for the best clustering measures. In...

this paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (fpso) and fuzzy c-means (fcm) algorithms, to solve the fuzzyclustering problem, especially for large sizes. when the problem becomes large, thefcm algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. the pso algorithm does find ago...