Mobile impromptu Networks has more difficult vulnerabilities compared with wired networks. Mobile impromptu networking (MANET) has become a vital technology in current years attributable to the speedy proliferation of wireless devices. They’re extremely at risk of attacks thanks to the open medium, dynamically ever-changing topology and lack of centralized watching purpose. It’s vital to look n...

Data generated in the fields of science, technology, business and in many other fields of research are increasing in an exponential rate. The way to extract knowledge from a huge set of data is a challenging task. This paper aims to propose a hybrid and viable method to deal with an information system in data mining, using topological techniques and the significance of the attributes measured u...

  For efficiency evaluation of some of the Decision Making Units that have uncertain information, Rough Data Envelopment Analysis technique is used, which is derived from rough set theorem and Data Envelopment Analysis (DEA). In some situations rough data alter nonradially. To this end, this paper proposes additive rough–DEA model and illustrates the proposed model by a numerical example.

In this paper, for the first time, we introduce and study the new concepts near closure operators induced from binary relation. These operators represent a generalization to closure operators that are induced from binary relations. The suggested techniques will narrow the gap between topologists and those who are interested in applications with topology in their field. The fundamental propertie...

We derive an invariance principle for the lift to rough path topology of stochastic processes with delayed regenerative increments under optimal moment condition. An interesting feature result is emergence area anomaly, a correction term in second level limiting which identified as average on regeneration interval. A few applications include random walks environment and additive functionals rec...

Rough data envelopment analysis (RDEA) evaluates the performance of the decision making units (DMUs) under rough uncertainty assumption. In this paper, new discussion regarding RDEA is extended. The RSBM model is proposed by integrating SBM model and rough set theory. The process of reaching solution is presented and this model is applied to efficiency evaluation of the DMUs with uncertain ...

Optimizing a neural network's topology is a difficult problem for at least two reasons: the topology space is discrete, and the quality of any given topology must be assessed by assigning many different sets of weights to its connections. These two characteristics tend to cause very "rough." objective functions. Here we demonstrate how self-assembly (SA) and particle swarm optimization (PSO) ca...

In a soft environment, we investigated several (classical) structures such as ideals, filters, grills, etc. It is well known that these are applied to expand abstract concepts; in addition, some of them offer vital tool address practical issues, especially those related improving rough approximation operators and accuracy measures. Herein, contribute this line research by presenting novel type ...

There are situations that Decision Making Units (DMU’s) have uncertain information and their inputs and outputs cannot alter redially. To this end, this paper combines the rough set theorem (RST) and Data Envelopment Analysis (DEA) and proposes a non-redial Rough-DEA (RDEA) model so called additive rough-DEA model and illustrates the proposed model by a numerical example.  

Considering a commutative unital quantale L as the truth value table and using the tool of L-generalized convergence structures of stratified L-filters, this paper introduces a kind of fuzzy upper topology, called fuzzy S-upper topology, on L-preordered sets. It is shown that every fuzzy join-preserving L-subset is open in this topology. When L is a complete Heyting algebra, for every completel...