Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...

in this paper we have proposed an approach for emotion detection in implicit texts. we have introduced a combinational system based on three subsystems. each one analyzes input data from a different aspect and produces an emotion label as output. the first subsystem is a machine learning method. the second one is a statistical approach based on vector space model (vsm) and the last one is a key...

in this study a machine learning algorithm was applied in order to develop a predictive model for the changes in phytoplankton biomass (chlorophyll a) in the lower nakdong river, south korea. we used a “hybrid evolutionary algorithm (hea)” which generated model consists of three functions ‘if-thenelse’ on the basis of a 15-year, weekly monitored ecological database. we used the average ...

The reflections recorded on satellite images have been affected by various environmental factors. In these images, some of these factors are combined with other environmental factors that cannot be distinguished. Therefore, it seems wise to model these environmental phenomena in the form of hybrid indicators. In this regard, satellite imagery and machine learning methods can play a unique role ...

In this work, several machine learning techniques are presented for nanofiltration modeling. According to the results, specific errors are defined. The rejection due to Nanofiltration increases with pressure but decreases with increasing the concentration of chloride ion. Methods of machine learning represent the rejection of nanofiltration as a function of concentration, pH, pressure and also ...

artificial immune systems (ais) can be defined as soft computing systems inspired by immune system of vertebrates. immune system is an adaptive pattern recognition system. ais have been used in pattern recognition, machine learning, optimization and clustering. feature reduction refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encoun...