Continuous K nearest neighbor queries (C-KNN) are defined as finding the nearest points of interest along an entire path (e.g., finding the three nearest gas stations to a moving car on any point of a pre-specified path). The result of this type of query is a set of intervals (or split points) and their corresponding KNNs, such that the KNNs of all points within each interval are the same. The ...

The available studies for estimating the characteristics of hydraulic jump are only for artificial or natural beds, and very limited researches have simultaneously considered artificial and natural beds. The aim of this study is to present comprehensive equations and models for predicting the characteristics of hydraulic jump in artificial and natural rough beds with various dimensions, arrange...

proper forest management needs quantitative and precise estimates of forest stands characteristics. remotely sensed imageries, due to accurate and broad spatial information, has become a cost-effective tool in forest management. classification of forest attributes and generation of thematic maps are among the common applications of remote sensing. the objective of this study was to optimize the...

k-nearest neighbor (kNN) is a widely used learning algorithm for supervised tasks. In practice, the main challenge when using kNN its high sensitivity to hyperparameter setting, including number of nearest neighbors k, distance function, and weighting function. To improve robustness hyperparameters, this study presents novel method based on graph neural network, named kNNGNN. Given training dat...

In the present work, an artificial neural network (ANN) model was used to study the quantitative structure retention relationship (QSRR) of retention index (RI) of some volatile compounds in natural cocoa and conched chocolate powder. Molecular structural descriptors are selected using genetic algorithm to construct the nonlinear QSRR models, kernel partial least squares PLS (KPLS) and Levenber...

Spectral clustering is a well-known graph-theoretic algorithm. Although spectral has several desirable advantages (such as the capability of discovering non-convex clusters and applicability to any data type), it often leads incorrect results because high sensitivity noise points. In this study, we propose robust algorithm known KNN-SC that can discover exact by decreasing influence To achieve ...

The existence of machine learning has been exploited to solve difficulties in various fields, including the classification leaf species agriculture. Betel is one plants that provide health advantages. objective using a approach classify betel species. This study involved several processes: image acquisition, region interest (ROI) detection, pre-processing, feature extraction, and classification...

Organizations expose to financial risk that can lead to bankruptcy and loss of business is increased nowadays. This may leads to discontinuity in operations, increased legal fees, administrative costs and other indirect costs. Accordingly, the purpose of this study was to predict the financial crisis of Tehran Stock Exchange using neural network and genetic algorithm. This research is descripti...