in this study, several data-driven techniques including system identification, adaptive neuro-fuzzy inference system (anfis), artificial neural network (ann) and wavelet-artificial neural network (wavelet-ann) models were applied to model rainfall-runoff (rr) relationship. for this purpose, the daily stream flow time series of hydrometric station of hajighoshan on gorgan river and the daily rai...

Brushless DC (BLDC) motors are the most popular used by industry because they easy to control. BLDC generally controlled artificial controls such as Fuzzy Logic Controller (FLC), Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS). However, performance of control system in previous studies was compared separately with their respective parameters, making it difficu...

Taking an intelligent trimming device hydraulic manipulator as the research object, aiming at uncertainty, nonlinearity and complexity of its system, a trajectory tracking control scheme is studied in this paper. In light virtual work principle, coupling dynamic model system established. order to improve anti-interference adaptive abilities compound strategy combining neuro-fuzzy inference (ANF...

Accurate solar radiation (SR) prediction is one of the essential prerequisites harvesting energy. The current study proposed a novel intelligence model through hybridization Adaptive Neuro-Fuzzy Inference System (ANFIS) with two metaheuristic optimization algorithms, Salp Swarm Algorithm (SSA) and Grasshopper Optimization (GOA) (ANFIS-muSG) for global SR at different locations North Dakota, USA...

This paper proposes adaptive neuro-fuzzy inference system (ANFIS) to predict the risk with its aggregated cost (CR) of an accident in road transportation hazardous material, aim is provide a more accurate and reliable data for safety transportation. The determination index by conventional methods such as Risk graphs deterministic approaches may lead imprecise values due uncertainties, both para...

Conventional control techniques are not able to accomplish the stable cooling in vapor compression air conditioning system. This paper describes the fuzzy models of refrigerating compressor, expansion valve, evaporator and condenser as basic elements of vapor compression air conditioning system. Compressor speed, delivery pressure, refrigerant flow rate, valve opening area, pressure difference ...

The investigation of the effects of cracks or similar weaknesses on the load carrying capacity of structural elements such as columns, beams and shells is an important problem in civil, mechanical, earthquake and aerospace engineering. In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN)model have been successfully used for the buckling analysis of sl...

The paper presents a methodology for developing adaptive speed controllers in a permanent-magnet brushless DC (BLDC) motor drive system. A proportional-integral controller is employed in order to obtain the controller parameters at each selected load. The resulting data from PI controller are used to train adaptive neuro-fuzzy inference systems (ANFIS) that could deduce the controller parameter...

This paper proposed a novel adaptive neuro-fuzzy inference system (ANFIS), which combines subtract clustering, employs adaptive Hamacher T-norm and improves the prediction ability of ANFIS. The expression of multiinput Hamacher T-norm and its relative feather has been originally given, which supports the operation of the proposed system. Empirical study has testified that the proposed model ove...

Most of the earlier studies in the inventory control and management make assumption that the manufacturing system is reliable and does not fail. However, in the real industrial applications, there is no completely reliable manufacturing system; Machine failure occur and the production does not resume before repair. In this paper we will study and analyze the optimal lot size in a real productio...