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Bus Transportation plays an important role in modern society and has been developed in many parts of the world. It reduces the private vehicle usage; fuel consumption and more over reduce traffic congestion, if the arrival time of the buses is accurate. In this paper, various literatures have been surveyed which is used for prediction of bus arrival time. Real time prediction of arrival time is so...
The growing demand for smarter high-performance embedded systems leads to the integration of multiple functionalities in on-chip systems with tens (even hundreds) of cores. This trend opens a very challenging question about the optimal resource allocation in those manycore systems. Answering this question is key to meet the performance and energy requirements. This paper deals with a learning technique...
Energy consumption is the key indicator of speed control technology for improving energy efficiency of belt conveyor systems. This paper presents the design and verification of a short-term mathematical model intended for the prediction of energy consumption of a belt conveyor system using neural network method. The obtained model corresponds with real operational conditions. It can take advantage...
This study established a survival prediction model for liver cancer using data mining technology. The data were collected from the cancer registration database of a medical center in Northern Taiwan between 2004 and 2008. A total of 227 patients were newly diagnosed with liver cancer during this time. With literature review, and expert consultation, nine variables pertaining to liver cancer survival...
Because of short duration, quick mutation, large randomness and many influencing factors of blasting seismic waves, variation characteristics for dominant frequency of blasting seismic signals have no obvious law to follow. Commonly experts only take two factors including maximal section explosive and blasting center distance into consideration for convenience. Prediction model for dominant frequency...
On the basis of the information fusion idea, a novel multiple information fusion modeling method is proposed. Several artificial neural networks are used to fuse the information of data. And then the results of information fusion by ANNs will be fused again according to their performance. Using the novel multiple information fusion scheme, a new modeling approach is presented to establish the prediction...
In long-term prediction, dealing with the relevant factors correctly is the key point to improve the wind power prediction accuracy. The key factors that affect the wind power prediction are identified by rough set theory and then the additional inputs of the prediction model are determined. To test the approach, the weather data from Beijing area are used for this study. The prediction results are...
Corrosion of reinforced concrete is a chronic infrastructure problem, particularly in areas with deicing salt and marine exposure. And the diffusion behavior of the chloride ions in concrete is a more complex and complicated transport process than what can be described by Fick's law of diffusion. To maintain structural integrity, a prediction model of radial basis function (RBF) network is presented...
The instability of the concentration of CO2 in the system of CO2 refining is controlled by the following means: recognizing the system by neural net work; building the prediction model and the technological parameters optimization model of the system; predicting the key producing parameters which affect the concentration of CO2 the most; optimizing and controlling the key producing parameters by the...
According to the floatation processing characteristic with time-variation, uncertainty and complicated nonlinear relations, a prediction method of concentrate grade and prediction model of ore dressing date is proposed. This article establish a prediction model of ore dressing date based on Jordan neural network including input of influence factors and dynamic time sequence feedback of concentrate...
Soil water is the basic condition of crop living. Soil water evaporation is not only main foundation of the management for water but also have an important effect on the regulation for temperature, humidity, environment and energy consumption in the greenhouse. Soil water even affect crop yields, qualities, and economy benefit of crop production. This paper analyzed main environment factors caused...
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...
Soil water is the basic condition of crop living. Soil water evaporation is not only main foundation of the management for water but also have an important effect on the regulation for temperature, humidity, environment and energy consumption in the greenhouse. Soil water even affect crop yields, qualities, and economy benefit of crop production. This paper analyzed main environment factors caused...
To make an accurate prediction about the amount of equipment maintenance materials consumption (EMMC), which plays an important role of equipment maintenance materials support, precondition and management, an LM algorithm prediction model of EMMC established based on the improved BP neural network algorithm by means of history data processing, and which has been discussed and verified through example...
In this paper, through combining information diffusion principle and BP neural network theory, a new prediction model of drought disaster assessment is established. First, the original data are fuzzily processed based on information diffusion method, then a new training sample is formed; second, the new sample is used to design and train BP neural network; finally, the trained fuzzy neural network...
This paper uses GMDH method to establish a prediction model to forecast the output value of transport & storage of Guangdong in China, since the original samples of the output value of transport & storage are less enough to be used with the traditional methods. Compared with traditional linear regression and artificial neural network, the predicted results show that GMDH method is an effective...
Surrounding rock pressure of tunnel is the key factor to analyze the stability of surrounding rock. However, the deformation of surrounding rock is affected by many factors among which there are intense non-linear relation, so it is difficult to predict it effectively. In this paper, the method based on chaos neural network model is put forward, the feasibility of prediction techniques of combination...
Understanding and predicting human mobility is a crucial component of transportation planning and management. In this paper we propose a new model to predict the location of a person over time based on individual and collective behaviors. The model is based on the person's past trajectory and the geographical features of the area where the collectivity moves, both in terms of land use, points of interests...
Considering of the ill-posed problem in learning process of echo state network(ESN), a new learning algorithm of ESN is proposed based on regularization method. The regularization term provides a stable solution to function approximation with a tradeoff between accuracy and smoothness of the solutions. So the redundant weights of neural network are damped and converged to the zero state. The structure...
Sideslip angle is the most widely used attributes for measuring the vehicle side slipping. Predicting the trend of sideslip angle in advance is of great significance for sideslipping precaution. In this research, small-vehicle model was selected, took steering wheel angle, yaw rate, lateral acceleration and four wheel velocities into account, and then applied neural network to build a prediction model...
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