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Established the computational model about the safe distance of vehicles. In order to simulate the dynamic model of rear-end, based on VB software to build a freeway rear-end simulation system. Simulation system provides an important means for in-depth study on rear-end probability. To investigate the non-linear relationship of probability and impact factors of rear-end, established probability of...
A forecasting model for gas emission based on wavelet neural network is proposed in this paper. In the model, wavelet neutral network (WNN) is applied to the forecasting with gradient descent and amended by validity of iteration training algorithm. Compared with back-propagation neural networks, forecasting of the model has advantages of faster convergence and more accurate. Simulation results have...
The generalization ability of neural network is an important aspect affecting its application. Meanwhile, the selection of training samples has a great impact on this ability. In order to improve the completeness of training samples, a method of samples self-learning of BP neural network based on clustering is put forward in this paper. By using the method of clustering, new samples can be collected...
The paper set up regional logistics prediction model based on the chaotic nerve network according to regional logistics characteristic, judge regional logistics chaotic characteristic Utilize phase space reconstruction technology at first, Positive Lyapunov exponent and correlation dimension prove the regional logistics has Chaotic characteristics. Then set up neural network prediction models on the...
In this paper, the off-line Chinese character image is transformed into ellipse shape of basic Chinese characters strokes in different position. The stroke "turning" and joint or crossover of strokes is combined by basic strokes. The neural network for extracting Chinese character has been build up. The research on off-line Chinese character image is transformed into the research on double...
The thermo-gravimetric data were employed for investigating the activity as well as the capacity of Ca-based sorbent. The TGA data confirmed the fact that the carbonation reaction involves two distinct different stages including a fast kinetically controlled process followed by a slow one governed by diffusion, moreover the reaction rate and conversions were depended on the physic characteristics...
Land cover change assessment is one of the main applications of remote sensed data. Change in forest cover have widespread effects on the provision of ecosystem services, and provide important feedbacks to climate change and biodiversity. Moreover, it will be extremely critical if the accuracy of image interpretation can be improved for better understanding the change of forest. Parametric methods...
Wind power prediction is of great importance for the safety, stabilization and economic efficiency of electric power grids, especially when the wind power penetration level of the gird is high. ANN (Artificial Neural Network) is an appropriate method for wind power prediction. But the generalization of common ANN is poor and the prediction precision is not stable. Neural network ensemble can enhance...
This paper proposes a composite method for short-term load forecasting, which is based on fuzzy clustering wavelet decomposition and BP neural network. Firstly, the similar-day's load is selected as the input load based on the fuzzy clustering method; secondly, the wavelet method is applied to decompose the similar-day load into the low frequency and high frequency components, from which the feature...
Wind power is a significant alternate energy in times of energy crisis. In virtue of its intermittency and fluctuation, it poses several operational challenges to grid interfaced wind energy systems. This paper introduced autoregressive integrated moving average (ARIMA) model and artificial neural network (ANN) to forecast the hourly wind speed one to four hours ahead. The models are applied to wind...
Following a number of studies that have employed different forms of neural network models to perform dissolved gas-in-oil analysis (DGA) of transformer bushings, this manuscript focuses on evaluating the relevance of the parameters that form part of the model input space. Using a multilayer neural network initially populated with all the 10 input parameters (10V-Model), a matrix containing causal...
This paper discusses on the adaptive neural network model for predicting the energy consumption at a metering station. The function of the metering system is to calculate the energy consumption of the outgoing gas flow. To ensure the robustness of the developed model, it is suggested to make the model an adaptive model that will periodically update the weights. This will ensure the reliability of...
This paper presents the performances of different type fuzzy logic controllers which are adaptive neural-network based fuzzy logic (ANNFL) controller, hierarchical adaptive neural-network based fuzzy logic (HANNFL) controller and adaptive neural-network based interval type2 fuzzy logic (ANNIT2FL) controller. ANNFL, HANNFL and ANNIT2FL controllers are applied on flexible manipulator for both position...
Improving the diversity of Neural Network Ensembles (NNE) plays an important role in creating robust classification systems in many fields. Several methods have been proposed in the literature to create such diversity using different sets of classifiers or using different portions of training/feature sets. Neural networks are often used as base classifiers in multiple classifier systems as they adapt...
Artificial Neural Networks (ANNs) have been used as a promising tools for many applications. In recent years, a computer-aided design approach based on ANNs has been introduced to microwave modeling, simulation and optimization. In this work, the characteristics parameters of the conductor-backed asymmetric coplanar waveguide (CB - ACPW) with one lateral ground plane have been determined with the...
Radio Frequency microelectromechanical system (RF MEMS) is a relatively new field which has generated a tremendous amount of excitement because of its performance enhancement and low manufacturing cost. RF MEMS switch is a fundamental device that offers wide applications in defense and telecommunication systems. In this paper we propose an efficient approach based on Artificial Neural Network (ANN)...
This paper takes a kind of ceramic glaze as an example, and builds an improved BP neural network model for optimizing the formulation on ceramic glaze. The improved BP neural network adopts Levenberg-Marquardt algorithms. The paper reviews how to build the ceramic formulation optimization model based on BP artificial neural network, including the establishment of neural network, the training, and...
Renewable energy sources are becoming a viable substitute for conventional energy sources due to increases in world's energy demand and scarce resources. Solar pump operated with AC drive offer better choice in terms of size, ruggedness, efficiency and maintainability. In this work, dc power from solar panel is boosted and fed to an inverter which gives ac output. Inverter drives the motor coupled...
A MANET is a collection of mobile nodes that organize themselves into a network without any predefined infrastructure or centralized operation management and because of its especial features, is vulnerable to security attacks. In recent years, different approaches are implemented to improve the security level of MANET. The aim of this paper is to design a mechanism of intrusion detection in the MANET...
The piece of research presents a conceptual overview on diverse cognitive styles reflections in adaptable Open Learning systems. The main goal of this approach is quantitative forecasting the performance of adaptable Open Learning (equivalently e-learning) Systems using cognitive Neural Network modelling. Furthermore, analysis of interactive two diverse learners' cognitive styles with a friendly adaptable...
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