In this document, the development and experimental validation of a nonlinear controller with an adaptive disturbance compensation system applied on quadrotor are presented. The introduced scheme relies generalized regression neural network (GRNN). proposed has structure consisting inner control loop inaccessible to user (i.e., embedded controller) outer which generates commands for loop. GRNN i...

Machine learning (ML) models, including artificial neural networks (ANN), generalized regression (GRNN), and adaptive neuro-fuzzy interface systems (ANFIS), have received considerable attention for their ability to provide accurate predictions in various problem domains. However, these models may produce inconsistent results when solving linear problems. To overcome this limitation, paper propo...

Construction crew productivity prediction is one of the most important issues that affect realistic construction duration and cost. Use different search algorithms like Feed Forward Neural Network, Ant Colony, Artificial Bee Particle Swarm Optimization, Radial Based Networks Self Organizing Maps for problem have been discussed in previous studies. However, significant effect coherence between n...

Condit ion m onitoring (CM) of gearboxes is a necessary act ivit y due to the crucial im portance of gearboxes in power t ransm ission in m ost indust rial applicat ions. There has long been pressure to im prove m easuring techniques and develop analyt ical tools for early fault detect ion in gearboxes. This thesis develops new gearbox m onitoring m ethods by dem onst rat ing that operat ing pa...

This study offers a description and comparison of the main models of Artificial Neural Networks (ANN) which have proved to be useful in time series forecasting, and also a standard procedure for the practical application of ANN in this type of task. The Multilayer Perceptron (MLP), Radial Base Function (RBF), Generalized Regression Neural Network (GRNN), and Recurrent Neural Network (RNN) model...

As a kind of clean and renewable energy, wind power is winning more and more attention across the world. Regarding wind power utilization, safety is a core concern and such concern has led to many studies on predicting wind speed. To obtain a more accurate prediction of the wind speed, this paper adopts a new hybrid forecasting model, combing empirical mode decomposition (EMD) and the general r...

A new empirical technique to construct predictive models of vacuum pyrolysis process is presented in this study. Pyrolysis of biomass for preparing bio-oil was studied on a vacuum pyrolysis system, where rape straw was chosen as the raw material. The experiments ran based on orthogonal experimental design method. The operation factors of the system including pyrolysis temperature, system pressu...