H.5. Image Processing and Computer Vision
1. A Novel Face Detection Method Based on Over-complete Incoherent Dictionary Learning

S. Mavaddati

Volume 7, Issue 2 , Spring 2019, , Pages 263-278

Abstract
  In this paper, face detection problem is considered using the concepts of compressive sensing technique. This technique includes dictionary learning procedure and sparse coding method to represent the structural content of input images. In the proposed method, dictionaries are learned in such a way that ...  Read More

H.6.2.4. Neural nets
2. Intelligent identification of vehicle’s dynamics based on local model network

M. Abtahi

Volume 7, Issue 1 , Winter 2019, , Pages 161-168

Abstract
  This paper proposes an intelligent approach for dynamic identification of the vehicles. The proposed approach is based on the data-driven identification and uses a high-performance local model network (LMN) for estimation of the vehicle’s longitudinal velocity, lateral acceleration and yaw rate. ...  Read More

F.2.11. Applications
3. Estimating scour below inverted siphon structures using stochastic and soft computing approaches

M. Fatahi; B. Lashkar-Ara

Volume 5, Issue 1 , Winter 2017, , Pages 55-66

Abstract
  This paper uses nonlinear regression, Artificial Neural Network (ANN) and Genetic Programming (GP) approaches for predicting an important tangible issue i.e. scours dimensions downstream of inverted siphon structures. Dimensional analysis and nonlinear regression-based equations was proposed for estimation ...  Read More

G.2. Models and Principles
4. Governor design for hydropower plants by intelligent sliding mode variable structure control

D. Qian; L. Yu

Volume 4, Issue 1 , Winter 2016, , Pages 85-92

Abstract
  This work proposes a neural-fuzzy sliding mode control scheme for a hydro-turbine speed governor system. Considering the assumption of elastic water hammer, a nonlinear mode of the hydro-turbine governor system is established. By linearizing this mode, a sliding mode controller is designed. The linearized ...  Read More