Review and Analysis of Machine Learning and Soft Computing Approaches for User Modeling

Abstract

ABSTRACT

Prediction of Anger Expression of Individuals with Psychiatric Disorders using the Developed Computational Codes based on the Various Soft Computing Algorithms

“…In the similar published papers, some researchers have tried to recognize the human emotions or behavior using soft computing algorithms like artificial neural network and neuro-fuzzy systems. The accuracy of the predicted values using DT, RBF and ANFIS in the present study is in the range or better than the previously published works performed works using artificial neural network or neuro-fuzzy algorithms (Chatterjee & Shi, 2010;Devi et al, 2016;Ioannou et al, 2005;Kalghatgi et al, 2015;Lee et al, 2006;Malkawi & Murad, 2013;Nicholson, Takahashi, & Nakatsu, 2000;Potey & Sinha, 2015;Sprengelmeyer, Rausch, Eysel, & Przuntek, 1998;Subramanian, Suresh, & Babu, 2012). The main superiority of the soft computing algorithms like DT, RBF and ANFIS in comparison to numerical methods is that it could be used for modeling of any complex system in order to forecast or control a desired parameters.…”

“…The artificial neural network and other soft computing algorithms were used as an important tool for the understanding of psychological phenomena and cognitive psychology (Levine, 1989; Martindale, 1991). The use of soft computing in various applications of psychology has continued over the years and it has grown significantly in the recent years (Almeida & Azkune, 2018; Devi, Kumar, & Kushwaha, 2016; Kalghatgi, Ramannavar, & Sidnal, 2015; Potey & Sinha, 2015). Application of artificial neural network for personality prediction (Kalghatgi et al, 2015), the use of the various approaches of user modeling, machine learning and soft computing techniques for modeling the human behavior (Potey & Sinha, 2015), application of ANFIS in the prediction of the anxiety of students (Devi et al, 2016) and development of the multilevel conceptual model for describing the user behavior using actions, activities, and intra- and inter-activity behavior (Almeida & Azkune, 2018) are examples of researches performed using the soft computing algorithms for prediction of human emotion and behavior in the psychology.…”

Intelligent Authentication for Identity and Access Management: A Review Paper

“…An Intelligent system has the ability to recognize and capture useful information from an object that is changed, it is already familiar with the original one [12]. So, it could possibly define Soft computing as an approach to invent computationally intelligent systems that is tolerant of imprecision, uncertainty, randomness, and partial truth [13] based on artificial intelligence techniques that provide efficient and feasible solutions in comparison with hard computing. These techniques are integrated to find intelligent solutions for the problems which are complex and need hybridized methods that are similar to human thinking in solving a problem [14].…”