this research was conducted to investigate spatial variability and estimate tree attributes in a plantation forest in the caspian region of iran using geostatistical analysis. sampling was performed based on a 50m?125m systematic grid in a maple stand (acer velutinum boiss) 18 years of age using circular samples of 200m2 area. totally, 96 sample plots were measured in 63 hectares and 14.25 hect...

Since big data sets are structurally complex, high-dimensional, and their attributes exhibit some redundant irrelevant information, the selection, evaluation, combination of those large-scale pose huge challenges to traditional methods. Fuzzy rough have emerged as a powerful vehicle deal with uncertain fuzzy in problems that involve very large number variables be analyzed short time. In order f...

The attribute dependence graph of a syntax tree may be partitioned into disjoint regions. Attribute instances in diierent regions are independent of one other. The advantages of partitioning the attribute dependence graph include simplifying the attribute grammar conceptually and allowing the possibility of parallel evaluation. We present a static partitioning algorithm for attribute grammars. ...

Handling missing attribute values is the greatest challenging process in data analysis. There are so many approaches that can be adopted to handle the missing attributes. In this paper, a comparative analysis is made of an incomplete dataset for future prediction using rough set approach and random tree generation in data mining. The result of simple classification technique (using random tree ...

Compiler optimizations can be described by tree transformations that replace complicated and non-efficient tree structures by equivalent but simpler and more efficient tree structures. For the specification of such tree transformations the classical attribute grammar framework has to be extended with conditional tree transformation rules, where predicates on attribute values (carrying context i...

Human-Namable visual attributes are promising in leveraging various recognition tasks. Intuitively, the more accurate the attribute prediction is, the more the recognition tasks can benefit. Relative attributes [1] learns a ranking function per attribute which can provide more accurate attribute prediction, thus, show clear advantages over previous binary attribute. In this paper, we inherit th...