We consider the nonparametric kernel estimation of the conditional cumulative distribution function given a functional covariate. Given the bias-variance trade-off of the risk, we first propose a totally data-driven bandwidth selection device in the spirit of the recent Goldenshluger-Lepski method and of model selection tools. The resulting estimator is shown to be adaptive and minimax optimal:...

this study recommends a gis-based (geographic information systems) and multi-criteria evaluation for site selection of gas power plant in natanz city of iran. the multi-criteria decision framework integrates legal requirements and physical constraints related to environmental and economic concerns. it also builds a hierarchy model for gas power plant suitability. the methodologies used for site...

* Abstract problems of Location Selection. Although no list can be considered exhaustive, Moore’s [1] enunciation of criteria still appears pertinent and can be considered as a fundamental basis for selection. Table 1 encapsulates some common criteria for selection. This paper uses the well-established Fuzzy C-Means Clustering Algorithm for suggesting a heuristic that effectively zeroes down up...

â  industrial site selection is a complicated decision and is related to various factors, so it is kind of multi-criteria decision analysis which is used for prioritizing different factors and selecting the best alternative among possible alternatives. in fact by scientific site selection, it is possible to minimize negative impacts of industrial construction and going towards sustainable devel...

The main purpose of this paper is to present a fuzzy multi-criteria decision making (FMADM) model for appropriate location selection of a health center. Therefore, we identify sixteen criteria and sub-criteria for selecting a health center location. These criteria and sub-criteria have been obtained from literature reviews and practical interviews. This paper proposes a method which combines th...

In this paper, principles and existing feature selection methods for classifying and clustering data be introduced. To that end, categorizing frameworks for finding selected subsets, namely, search-based and non-search based procedures as well as evaluation criteria and data mining tasks are discussed. In the following, a platform is developed as an intermediate step toward developing an intell...

In this paper, principles and existing feature selection methods for classifying and clustering data be introduced. To that end, categorizing frameworks for finding selected subsets, namely, search-based and non-search based procedures as well as evaluation criteria and data mining tasks are discussed. In the following, a platform is developed as an intermediate step toward developing an intell...