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Because of rare earth futures stock variability and uncertainty of the market, many investors hope to be able to predict the price of rare earth futures on the stock market in the future. The neural network does do better than others in short-term forecasting, and there is no need to establish a complex nonlinear mathematical model and relationship. Based on these advantages, this paper uses the neural...
Nowadays, public bicycle system has emerged as a good solution to terminal traffic. Compared with other public transportation systems (like bus or taxi), public bicycle system is clean, cheap, flexible and convenient. In particular, public bicycle doesn't need to follow fixed schedule. However, this flexibility of public bicycle system also brings in a problem: we don't know whether there exist available...
Fuzzy neural networks are found to be universal approximators when all the parameters of the network are adjusted simultaneously. Therefore, they have been used extensively classification and regression problems. Normally FNN uses TSK-type fuzzy rules where the consequent part of the rule base comprises linear terms. Thus FNNS may not be able to effectively handle chaotic time series like stock or...
The issue of PM2.5 is becoming a popular atmospheric research hotpot recently. This particular paper evaluates the era reasons as well as influencing factors associated with PM2.5 based on the information associated with PM2.5 in Xing Tai (2014. 01. 01 - 2014. 04. 26), and builds the actual era as well as evolution mode of PM2.5 in Xing Tai by utilizing evolutionary algorithms formula and BP neuron...
In this paper, a distributed photovoltaic (PV) power forecasting method is proposed by using genetic algorithm based neural network approach. With the large-scale application of PV power generation in the applications of society, and the characteristic of volatility and intermittent, and power forecasting of PV distributed have played a more important role in research of control strategies for microgrid...
The scientific and accurate forecast of air traffic flow is not only an effective protection to maintain the air traffic flow continued and unimpeded, and also is an important basis for the air traffic flow management(ATFM) to make decisions and development strategies. Based on the character of flow prediction, the prediction method of genetic algorithm to optimize wavelet neural network is proposed...
During the sewage treatment process, the biological reaction pool is able to obtain enough dissolved oxygen by aeration. Micro-organisms in the biological reaction pool rely on dissolved oxygen to decompose organic matter in sewage into inorganic matter, so that the sewage is purified. The control of dissolved oxygen concentration is a complex nonlinear process and it is difficult to establish the...
A modeling method based on genetic neural network used for book purchasing is put forward on account of lacking of a set of scientific and uniform purchasing mode and model in current book purchasing process. This method improves standard genetic algorithm first, and then uses the improved standard genetic algorithm as a method of feed forward neural network training and threshold value of feed forward...
Prediction of dengue outbreak becomes crucial in Malaysia because this infectious disease remains one of the main health issues in the country. Malaysia has a good surveillance system but there have been insufficient findings on suitable model to predict future outbreaks. While there are previous studies on dengue prediction models in Malaysia, unfortunately some of these models still have constraints...
Pointing at the problem that the spares consumption quota has been using the experience to develop, which makes spares application random and blind, this paper puts forward to build the reasonable lifeless-repairable spares consumption quota model. Analyze and determine the factors influencing the lifeless-repairable spares consumption, use BP neural network to predict, and use genetic algorithm to...
Daily solar radiation prediction is a nonlinear and non-stationary process. It's hard to model with a single method. A Genetic Algorithm Optimization of Wavelet Neural Network (GAO-WNN) model was set in this paper. The nonlinear process of daily solar radiation was forecasted by neural network and the non-stationary process of daily solar radiation was decomposed into quasi-stationary at different...
This thesis presents a BP Artificial neural network prediction modeling method for forecasting the trend of Shanghai index, and then uses the genetic algorithm to optimize the BP network parameters, weight and structure. The forecasting results show that the optimization algorithm not only avoids BP algorithm into a local minimum point and the problems of slow convergence, but also overcome the GA...
From the current economic climate results in fluctuations of currency exchange rates in all countries. Since the most countries use U.S. Dollar as the reference exchange rate. The exchange rate will change from time to time so variety of factors which affect the exchange rate forecasting in the exchange rates in advance are critical to evaluate for the impact of the economic system of each country...
The accurate and reliable Trip-generation Forecasting Model is the most basic and important part of the traffic forecasting model. This paper focuses on combining the neural network which has a strong fitting capability and genetic algorithm which has an excellent Global search capability with trip-generation forecasting model in order to achieve the purpose of improving the accuracy of prediction...
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