infiltration plays an important role in surface and subsurface hydrology and it is a key factor in the rainfall and runoff equations. the use of new approaches that have no limitations of common theoretical and empirical methods to determine infiltration relationships, will minimize the necessity of time consuming and costly experiments to determine permeability values and will make it possible...

Traditional clustering methods assume that there is no measurement error, or uncertainty, associated with data. Often, however, real world applications require treatment of data that have such errors. In the presence of measurement errors, well-known clustering methods like k-means and hierarchical clustering may not produce satisfactory results. The fundamental question addressed in this paper...

Objective: Soil temperature serves as a key variable in hydrological investigations to determine soil moisture content as well as hydrological balance in watersheds. The ingoing research aims to shed lights on potential of artificial neural networks (ANNs) and Neuro-Fuzzy inference system (ANFIS) to simulate soil temperature at 5-100 cm depths. To satisfy this end, climatic and...

Objective: Soil temperature serves as a key variable in hydrological investigations to determine soil moisture content as well as hydrological balance in watersheds. The ingoing research aims to shed lights on potential of artificial neural networks (ANNs) and Neuro-Fuzzy inference system (ANFIS) to simulate soil temperature at 5-100 cm depths. To satisfy this end, climatic and...

Compressive spectral clustering combines the distance preserving measurements of compressed sensing with the power of spectral clustering. Our analysis provides rigorous bounds on how small errors in the affinity matrix can affect the spectral coordinates and clusterability. This work generalizes the current perturbation results of two-class spectral clustering to incorporate multiclass cluster...

coriolis mass flow meters are one of the most accurate tools to measure the mass flow in the industry. however, two-phase mode (gas-liquid) may cause severe operating difficulties as well as decreasing certitude in measurement. this paper presents a method based on fuzzy systems to correct the error and improve the reliability of these sensors in the presence of two-phase model fluid. definite ...

The field of approximation algorithms for clustering is a very active one and a large number of algorithms have been developed for clustering objectives such as k-median, min-sum, and sparsest cut clustering. For most of these objectives, the approximation guarantees do not match the known hardness results, and much effort is spent on obtaining tighter approximation guarantees [1, 4, 5, 8, 6, 9...

One of the main techniques used in data mining is data clustering, which has many applications in computer science, biology, and social sciences. Constrained clustering is a type of clustering in which side information provided by the user is incorporated into current clustering algorithms. One of the well researched constrained clustering algorithms is called microaggregation. In a microaggreg...