Unsupervised construction of human body models

Unsupervised Construction of Human Body Models Using Principles of Organic Computing

Unsupervised learning of a generalizable model of the visual appearance of humans from video data is of major importance for computing systems interacting naturally with their users and others. We propose a step towards automatic behavior understanding by integrating principles of Organic Computing into the posture estimation cycle, thereby relegating the need for human intervention while simul...

Estimation of pore water pressure in the body of earth dams during construction with intelligent models

One of the basic measures in managing the stability of earth dams is to accurately estimate the amount of pore water pressure in the body of the dam during and after its construction. In this study, three different models of artificial neural network (ANN), adaptive neural-fuzzy inference system (ANFIS) and gene expression programming (GEP) to estimate the pore water pressure in the body of Kab...

Evaluation of Iranian electronic products manufacturing industries using an unsupervised model, ARAS, SAW, and DEA models

Optimization of sediment rating curve coefficients using evolutionary algorithms and unsupervised artificial neural network

Sediment rating curve (SRC) is a conventional and a common regression model in estimating suspended sediment load (SSL) of flow discharge. However, in most cases the data log-transformation in SRC models causing a bias which underestimates SSL prediction. In this study, using the daily stream flow and suspended sediment load data from Shalman hydrometric station on Shalmanroud River, Guilan Pro...

Simulation of Pore Water Pressure in the Body of Earthen Dams during Construction Using Combining Meta-Heuristic Algorithms and ANFIS

Accurate prediction of pore water pressure in the body of earth dams during construction with accurate methods is one of the most important components in managing the stability of earth dams. The main objective of this research is to develop hybrid models based on fuzzy neural inference systems and meta-heuristic optimization algorithms. In this regard, the fuzzy neural inference system and opt...