Small pelagic fishes particularly anchovy (Encrasicholina punctifer) and sardine (Sardinella sindensis) have an important role to support the Iranian fisheries, and are distributed along the entire length of the Persian Gulf and Oman Sea coastal waters. Using small pelagic fisheries logbook, a GIS-based environmental modelling approach was applied to investigate the presence and abundance of an...

Collection of appropriate qualitative and quantitative data is necessary for proper management and planning. Used the suitable inventory methods is necessary and accuracy of sampling methods dependent the inventory net and number of sample point. Nearest neighbor sampling method is a one of distance methods and calculated by three equations (Byth and Riple, 1980; Cotam and Curtis, 1956 and Cota...

Subspace clustering is a challenging task in the field of data mining. Traditional distance measures fail to differentiate the furthest point from the nearest point in very high dimensional data space. To tackle the problem, we design minimal subspace distance which measures the similarity between two points in the subspace where they are nearest to each other. It can discover subspace clusters...

Sample surveys typically gather information on a sample of units from a finite population and assign survey weights to the sampled units. Survey frequently have missing values for some variables for some units. Fractional regression imputation creates multiple values for each missing value by adding randomly selected empirical residuals to predicted values. Fractional imputation methods assign ...

the process of economic globalization and integration has had a tremendous growth in recent years and the convergence of various economic sectors, including the financial markets is increasingly in the spotlight. this increasing trend has strengthened investors' interests in the subject of convergence among the world's stock markets and investors experimentally show a passion for unde...

This paper presents a new hybrid classifier that combines the probability based Bayesian Network paradigm with the Nearest Neighbor distance based algorithm. The Bayesian Network structure is obtained from the data by using the K2 structural learning algorithm. The Nearest Neighbor algorithm is used in combination with the Bayesian Network in the deduction phase. For those data bases in which s...

This study sought to examine the relationship between self-reported time and distance to the nearest retail grocery store, healthy and unhealthy food consumption, and objectively measured body mass index (BMI). We conducted a survey with 1,503 racially diverse, low-income residents at five public health centers in Los Angeles County. Most participants reported shopping at a supermarket (86.7%) ...

A description is given of how to use an estimate of the maximum possible distance at which a nearest neighbor can be found to prune the search process in a depth-first branch and bound k-nearest neighbor finding algorithm.

We address the problem of replicating a Voronoi diagram V (S) of a planar point set S by making proximity queries: 1. the exact location of the nearest site(s) in S 2. the distance to and label(s) of the nearest site(s) in S 3. a unique label for every nearest site in S. In addition to showing the limits of nearest-neighbor database security, our methods also provide one of the first natural al...