An artificial neural network was trained to match soft-biometric features. A fuzzy logic inference engine performs smart decision fusion and authentication. Finally, a digital signal processor is used to embed the entire identification system. The embedded implementation demonstrates that improvement in ...
Standard neural network models consist of three layer networks with sigmoidal functions used as the ‘activation function' for each neuron in the hidden layer. However, networks which consist of linear combinations of radial basis functions offer significant theoretical and computational advantages over th...
artificial neural networksflood hazardThis study presents the development of Artificial Neural Networks (ANNs) and Fuzzy Logic (FL) models for prediction of daily reservoir inflow. Furthermore, a Linear Regression (LR) model was also developed as a traditional method for flood forecasting. To ...
In this paper, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used as maximum power point tracking controllers to improve the performance of a stand-alone photovoltaic system. Based on the FL-M-160W PV module specifications, the PV panel and the boost co...
fuzzy logic (FL)artificial neural network (ANN)multi-layer regression (MLR)statistical analysisIn this paper, the study aims to develop a model for predicting and budgeting maintenance and rehabilitation projects costs for residential buildings throughout their life cycle based on artificial neural ...
What is an Artificial Neural Network? These are computational models inspired by the human brain. Many of the recent advancements have been made in the field of Artificial intelligence, including Voice Recognition, Image recognition, and Robotics using it. They are the biologically inspired simulations...
However, the aforementioned numerical methods exhibit several drawbacks, such as the dependency of the final results on the initial conditions, implied extensive computations, possible fail convergence, and large data requirement. Artificial neural network and fuzzy logic techniques are also used to model...
Recently, more hybrid forecasting models have been proposed using ARIMA, Artificial Neural Networks (ANNs), and Fuzzy logic and applied to financial time series forecasting with good prediction performance. Pai and Lin [43] proposed a hybrid methodology to exploit the unique strength of ARIMA models...
With a single second-order neuron, any fuzzy logic operation, such as XOR, can be implemented. In this sense, any deep network constructed with quadratic neurons can be interpreted as a deep fuzzy logic system. Since traditional neural networks and second-order counterparts can represent each ...
Artificial neural network (ANN), fuzzy logic, and adaptive neuro-fuzzy inference system (ANFIS) algorithms are used to develop nine different flood prediction models using all the available training algorithms. The performance of the developed models is evaluated using multiple statistical performance ...