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As the largest agricultural country with a great amount of population, the cultivated land play an active role in protecting social stability and security during the process of building harmonious society, which is the material premise and necessary of humankind food-safety for our country and people lives. This paper predicted and analyzed the demand of infield in the future for Sichuan province...
Through the application of genetic algorithms (genetic algorithm, simplified as GA) and BP(Back Propation) neural network, I built a prediction model of roses diseases, in which I choose six indicators as the input of network, they are the minimum temperature, maximum temperature, average temperature, minimum humidity, maximum humidity, average humidity in the greenhouse, then I choose three diseases...
In order to obtain the law of the building settlement and forecast it effectively, neural network model was established for building settlement forecasting based on measured data, and an engineering example is shown to test and verify. Firstly, data of building settlement measured were normalized; embedding dimension was selected to establish the leaning samples. Mean square error (MSE) and mean absolute...
The time series model is decomposed into the trend items, cycle items and random items, respectively extracted by the establishment of the various forecasting model, the model is applied to the Chahayang farm in 1956 to 2008 on-year growth period crops fitting rainfall forecast, the results show that the model can reveal the crop growth period variation of monthly rainfall, for the rational development...
In order to simulate and analyze the schedule and cost of product development process (PDP) effectively, Design Structure Matrix was used as structural model in simulation. The schedule and cost models were described by triangular distribution of random variables. The disadvantage of traditional rework probability matrix was analyzed and the concept of rework conditional probability was proposed....
Information trap in demand chain management is looted in its network characteristics including multilevel linkages among partners, the transformation from supply chain to demand chain and the complexity of environment influence. The aim of this paper is to establish an integrative model to analyze four essential issues based on organizational network feature of demand chain. These issues are the collection...
As we all know, to predict the short-term traffic flow accurately and efficiently is the premise and key of traffic management and control. Based on these existing study, this paper selected BP neural network model in which the traffic flow difference was taken as the input parameter, applied the thought of dynamic rolling prediction to design a new short-term traffic flow prediction method, and wrote...
With the development and application of modern science and technology, many new technical measurement methods have been put forward successively which are of high resolution and high collection rate about microseismic monitoring. We urgently need an effective detection method of abnormal data (mine earthquake) to collect lots of data to make real-time detection. In the past, we usually depend on experienced...
Short-term load forecasting is important for electricity load planning and dispatches the loading of generating units in order to meet the electricity system demand. The precision of the load forecasting is related to electricity company's economic. This paper presents a approach named an autoregressive moving average (ARMA) cooperate with BP Artificial Neural Network (BPNN) approach, which can combine...
Microseismic monitoring means to records microseismic activities caused by the changes of the rock physical properties continuously through the high sensitivity seismic sensor placed in mine. How to make real-time detection of abnormal data in mine microseisms positioning system is a extremely important task. Forecast model and mechanism of data stream in the mine microcosmic monitoring system are...
Determining the weights in a combination forecasting is an important problem. We can translate the problem of computing weights into estimating the importance of attributes. Inclusion degree is one of the methods of computing importance of attributes. So this paper introduces a new method of computing weights based on inclusion degree. The example illustrates that the weights computed by inclusion...
To accurately obtain dynamic characteristics of a heat exchanger, black-box modeling method and gray-box modeling method were used with the help of neural network technology. The black-box model directly used the heat exchanger's input and output data to train the neural network. It constantly adjusted the network's weight to record the system's dynamic characteristics, and then predict output. Having...
The exact prediction of rockburst is an urgent problem for the underground excavation in high geostatic stress environment. Set pair analysis (SPA) and variable fuzzy sets (VFS) are new methodologies to describe and process system uncertainty. In this paper, a novel model using the theory of SPA is proposed to construct the difference function of VFS by means of approaching degree between the sample...
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