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This article explores the problems of automated retail systems, which named are vending machines. The main problem is the formation of an assortment of a vending machine, the realization of which will bring maximum profit. As a modern analysis tool of consumer demand in retail trade artificial intelligence is regarded. Attention is focused on one of the methods of constructing artificial intelligence...
The dynamic and system reliability of driving system in battery electric vehicles (BEVs) highly depend on the fault diagnosis technology. In this paper, we provided a new data compression approach and validated it on a method based on neural network (NN) to detect both failures' types and degree in drive system. In time-/frequency domain several statistical features were extracted from signals acquired...
In the previous study, we have investigated that the Extended Kalman Filter (EKF) has the excellennt performance and very fast learning as the training of Feedforward Neural Network (FNN). In the expansion of Kalman filter algorithm for nonlinear estimation, the Unscented Kalman Filter (UKF) was proposed. Enlightened the UKF is superior to EKF, in this study, we investigate the UKF algorithm as the...
The benefits of well-informed water management systems are related to the forecasting skills of hydrological variables. These benefits can be reflected in reducing economic and social losses to come. Therefore, the optimal design of water management projects frequently involves finding the methods or techniques that generate long sequences of hydrological data. These sequences considered as time series...
This paper presents a knee torque estimation in non-pathological gait cycle at stance phase. Comparative modelling by using dynamics model and neural network model is discussed. Dynamics modelling is constructed by using simple two degree of freedom dynamics with Newtonian calculation approach and more complex four degree of freedom dynamics with Lagrangian calculation approach. Neural network based...
Huge amount of data in today's world are stored in the form of electronic documents. Text mining is the process of extracting the information out of those textual documents. Text classification is the process of classifying text documents into fixed number of predefined classes. The application of text classification includes spam filtering, email routing, sentiment analysis, language identification...
In advanced wireless communication systems that require spectrally efficient modulation schemes, the modulated signal with a high peak-to-average power ratio (PAPR) drives the power amplifier (PA) to operate near the saturation region and introduces serious nonlinearity of the PA. Digital predistortion (DPD) is one of the most promising techniques for PA linearization. In this paper, we propose a...
Neural network is a kind of machine learning algorithm, applied in many ways. The traditional predictive guidance of aerocraft is hard to resolve the contradiction among robustness, real-time and the guidance of precision. The paper provides a predictive guidance algorithm for aerocraft, by combining neural network with predictive guidance to solve this problem. This research about the new style guidance...
The detection and elimination principle of redundant elements in the mathematical model is proposed in this paper. The efficiency of the proposed approach has been analyzed based on the neural network model of economic system and differential equations model. Results prove the 16 times increasing in the model accuracy.
The aim of the paper is to introduce a new approach for the Regions of Required Quality (RRQ) construction under the Control Systems computer-aided analysis and design. Application of the Artificial Neural Networks (ANNs) as a tool in the proposed techniques is represented under the title “Method of Sensitive Border”. The developed Neural network model of the RRQ-region's border allows one to get...
At present, the researches on credit risk analysis mainly focus on commercial bank loan or consumer credit risk, and there is little research about the credit risk of rural credit cooperatives. The purpose of this paper is to evaluate credit risk for the rural credit cooperatives using artificial neural network model. We establish credit risk assessment index system for rural credit cooperatives....
In this paper, a model predictive control strategy based on neural network is developed for the boost pressure tracking of a turbocharged gasoline engine. Firstly, the predictive model is trained by neural network due to its capacity of learning nonlinear process, institutive structure and simple training procedure. Secondly, the online linearization of neural network model is deduced by Taylor's...
Recurrent neural networks are represented as non-linear models of dynamic systems. This kind of neural networks is divided into two groups, which are globally and locally recurrent neural networks. Some types are distinguished among globally recurrent networks. The major approximation properties and features of every distinguished type are emphasized. The represented analysis is useful for choosing...
Wind energy has many advantages, because it does not pollute and is an inexhaustible source of energy. The Double Fed Induction Generator (DFIG) is one of the most important electric generator used for Horizontal Axis Wind Turbine (HAWT). In this paper, a Discrete-time Neural Input-Output Feedback Linearization Control (N-IOFLC) for DFIG is proposed to force the rotor currents to track specified reference...
This paper presents an approach of rotating machinery fault diagnosis based on Nonlinear Autoregressive with External (Exogenous) Input NARX neural networks. This tool is trained on the real data obtained from the sensors at bearing and it is used to ensure the faults diagnosis of the most damages that can appear in the system of gas turbine. Indeed the artificial neural networks provide an effective...
Camera calibration is necessary in machine vision application field. Calibration model has nonlinear characteristics, and establishment of mathematical model is often a complicated process, but neural network can solve the complex nonlinear problem effectively, neural network has strong nonlinear approximation ability, adaptive network parameters and fast learning. This paper presents a neurocalibration...
As a type of clean and renewable energy source, wind power is being widely used all around the world. However, owing to the uncertainty and instability of the wind power, it is important to build an accurate prediction model for wind power for the grid-connected security operation. The performance of hybrid method is always better than that of single ones in the wind power prediction. Actual wind...
Cognitive radio could detect the white space of spectrum and utilize spectrum resource efficiently. In a cognitive radio system, the recognition of signal modulation is a key technology, which would help the cognitive radio system to configure and realize intelligent green communication. In general, the recognition of signal modulation is not a linear classification. Back propagation (BP) neural network...
Students academic performance is the reflection of both academic background and family support. This performance record is critical for the educational institution because they can learn from this to improve their quality. Educational data mining helps to analyze these data and extract information from it. We can determine the status of learners academic performance. For achieving this we can use...
Gas hydrates can cause serious problems in oil and gas industry. Several measurements, connected to formation of gas hydrate, were performed on our department in last decade. Using the collected data, a preventive inhibitor dosing system can be developed, based on model driven system. The nature of the model is highly influence the quality of control system. In this article a model of gas hydrate...
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