Miloš Milovančević

AN APPLICATION OF MULTICRITERIA OPTIMIZATION TO THE TWO-CARRIER TWO-SPEED PLANETARY GEAR TRAINS

The objective of this study is the application of multi-criteria optimization to the two-carrier two-speed planetary gear trains. In order to determine mathematical model of multi-criteria optimization, variables, objective functions and conditions should be determined. The subject of the paper is two-carrier two-speed planetary gears with brakes on single shafts. Apart from the determination of the set of the Pareto optimal solutions, the weighted coefficient method for choosing an optimal solution from this set is also included in the mathematical model.

Precipitation concentration index management by adaptive neuro-fuzzy methodology

This paper reconsiders the precipitation concentration index (PCI) in Serbia using precipitation measurements such as the mean winter precipitation amount, annual total precipitation, mean summer precipitation amount, mean spring precipitation amount, mean autumn precipitation amount and the mean of precipitation for the vegetation period (April–September). Potentials for further improvement of PCI prediction lie in the improvement of current prediction strategies. One of the options is the introduction of model predictive control. To manage the PCI, it is good to select factors or parameters that are the most important for PCI estimation and prediction, i.e. to conduct variable selection procedure. In the present study, a regression based on the adaptive neuro-fuzzy inference system (ANFIS) is applied for selection of the most influential PCI inputs based on the precipitation measurements. The effectiveness of the proposed strategy is verified according to the simulation results. The results show that the mean autumn precipitation amount is the most influential for PCI prediction and estimation and could be used for the simplification of predictive methods to avoid multiple input variables.

DETERMINATION OF IMPORTANT PARAMETERS FOR PATENT APPLICATIONS

This research study is an analysis of patent applications based on different input parameters. Nine patent indicators for describing patent applications are retrieved from the World Bank database. The method of ANFIS (adaptive neuro fuzzy inference system) is applied to selecting the most important parameters for patent applications. The inputs are: charges for the use of intellectual property for payments and receipts, research and development expenditure, trademark applications for residents and nonresidents, researchers in research and development (R&D), technicians in R&D and high-technology exports. As the ANFIS outputs, patent applications for nonresidents and residents are considered. The results show that the combination of research and development expenditure and technicians in R&D is the most influential combination of input parameters for patent applications.

Cross-cultural dimensions influence on business internationalization by soft computing technique

Abstract Cultural difference plays an important role in industrialized business countries. The topic of cross-cultural management has become the topical area in modern business worldwide. Cross-cultural implication and cultural dimensions was analyzed using Hofstede model that consists of seven dimensions: Assertiveness, Future Orientation, Performance Orientation, Power Distance, Uncertainty Avoidance, Collectivism I (Institutional) and Collectivism II (In-Group). In the present paper, we investigate what impact business internationalization has on cross-cultural dimensions - specifically, gender egalitarianism forecasting and humane orientation. A soft computing method was applied for this analyzing. Combination of Collectivism I (Institutional) and Collectivism II (In-Group) was the most influential on the Gender Egalitarianism and the combination of Future Orientation and Performance Orientation was the most influential on the Humane Orientation in the business internationalization.

Vibration prediction of pellet mills power transmission by artificial neural network

Purpose The purpose of this study is to establish a vibration prediction of pellet mills power transmission by artificial neural network. Vibration monitoring is an important task for any system to ensure safe operations. Improvement of control strategies is crucial for the vibration monitoring. Design/methodology/approach As predictive control is one of the options for the vibration monitoring in this paper, the predictive model for vibration monitoring was created. Findings Although the achieved prediction results were acceptable, there is need for more work to apply and test these results in real environment. Originality/value Artificial neural network (ANN) was implemented as the predictive model while extreme learning machine (ELM) and back propagation (BP) learning schemes were used as training algorithms for the ANN. BP learning algorithm minimizes the error function by using the gradient descent method. ELM training algorithm is based on selecting of the input weights randomly of the ANN network and the output weight of the network are determined analytically.

Analyzing of micro-electro-mechanical systems (MEMS) sensor for pumping aggregates

Purpose The purpose of this research paper is to develop and analyze micro-electro-mechanical systems sensor for vibration monitoring of pumping aggregate. Design/methodology/approach The system is based on smart sensor and smart mobile phone. Findings The numerous measurements on a wide range of turbo aggregates were performed to establish the operating condition of pumping aggregates. Originality/value Afterwards, the influence of vibration at different positions on the output vibration of the pumping aggregate was analyzed by adaptive neuro fuzzy inference system method.

Optimization of vibro-diagnostic method for marine rotating pumps

Techno-economical optimization of vibro-diagnostic method implies defining of the minimal number of vibro-diagnostic information, which could be used for precise and definite diagnosis of broad spectra of failures or malfunctions with all types of rotating machines in standard use, including marine pumps. Economic optimization is done based on competitive advantage approach, but in coherence to technical aspect. Techno-economical optimization in this research is analysed more from the aspect of the optimization problem new formulation, then from the aspect of mathematical apparatus for solving the problem. In this case, the optimization is based on establishing the possibility of certain defect appearance at marine rotating machines and implementation of causal relations between diagnostic model and defined goal functions values.